\documentclass{article}
\author{Mike Hearn}
\date{\today}
\title{Corda: A distributed ledger}
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Version 1.0
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\begin{abstract}

A decentralised database with minimal trust between nodes would allow for the creation of a global ledger. Such a ledger
would have many useful applications in finance, trade, healthcare and more. We present Corda, a decentralised
global database, and describe in detail how it achieves the goal of providing a platform for decentralised app
development. We elaborate on the high level description provided in the paper \emph{Corda: An
introduction}\cite{CordaIntro} and provide a detailed technical discussion.

\end{abstract}
\vfill

\newpage
\tableofcontents
\newpage
\section{Introduction}

In many industries significant effort is needed to keep organisation specific databases in sync with each other.
In the financial sector the effort of keeping different databases synchronised, reconciling them to ensure
they actually are synchronised and resolving the `breaks' that occur when they are not represents a significant
fraction of the total work a bank actually does.

Why not just use a shared relational database? This would certainly solve a lot of problems using only existing technology,
but it would also raise more questions than answers:

\begin{itemize}
\item Who would run this database? Where would we find a sufficient supply of angels to own it?
\item In which countries would it be hosted? What would stop that country abusing the mountain of sensitive information it would have?
\item What if it were hacked?
\item Can you actually scale a relational database to fit the entire financial system?
\item What happens if the database needs to go down for maintenance? Does the economy stop?
\item What kind of nightmarish IT bureaucracy would guard schema changes?
\item How would you manage access control?
\end{itemize}

We can imagine many other questions. A decentralised database attempts to answer them.

In this paper we differentiate between a \emph{decentralised} database and a \emph{distributed} database. A distributed
database like BigTable\cite{BigTable} scales to large datasets and transaction volumes by spreading the data over many
computers. However it is assumed that the computers in question are all run by a single homogeneous organisation and that
the nodes comprising the database all trust each other not to misbehave or leak data. In a decentralised database, such
as the one underpinning Bitcoin\cite{Bitcoin}, the nodes make much weaker trust assumptions and actively cross-check
each other's work. Such databases trade performance and usability for security and global acceptance.

\emph{Corda} is a decentralised database platform with the following novel features:

\begin{itemize}
\item Nodes are arranged in an authenticated peer to peer network. All communication is direct. Gossip is not used.
\item New transaction types can be defined using JVM\cite{JVM} bytecode. The bytecode is statically analyzed and rewritten
on the fly to be fully deterministic, and to implement deterministic execution time quotas.
\item Transactions may execute in parallel, on different nodes, without either node being aware of the other's transactions.
\item There is no block chain\cite{Bitcoin}. Transaction races are deconflicted using pluggable \emph{notaries}. A single
Corda network may contain multiple notaries that provide their guarantees using a variety of different algorithms. Thus
Corda is not tied to any particular consensus algorithm. (\cref{sec:notaries})
\item Data is shared on a need-to-know basis. Nodes provide the dependency graph of a transaction they are sending to
another node on demand, but there is no global broadcast of \emph{all} transactions.
\item Bytecode-to-bytecode transpilation is used to allow complex, multi-step transaction building protocols called
\emph{flows} to be modelled as blocking code. The code is transformed into an asynchronous state machine, with
checkpoints written to the node's backing database when messages are sent and received. A node may potentially have
millions of flows active at once and they may last days, across node restarts and even certain kinds of upgrade. Flows expose progress
information to node administrators and users and may interact with people as well as other nodes. A library of flows is provided
to enable developers to re-use common protocols such as notarisation, membership broadcast and so on.
\item The data model allows for arbitrary object graphs to be stored in the ledger. These graphs are called \emph{states} and are the atomic unit of data.
\item Nodes are backed by a relational database and data placed in the ledger can be queried using SQL as well as joined
with private tables. States can declare a relational mapping using the JPA standard.
\item The platform provides a rich type system for the representation of things like dates, currencies, legal entities and
financial entities such as cash, issuance, deals and so on.
\item The network can support rapid bulk data imports from other database systems without placing load on the network.
Events on the ledger are exposed via an embedded JMS compatible message broker.
\item States can declare scheduled events. For example a bond state may declare an automatic transition to an
``in default'' state if it is not repaid in time.
\item Advanced privacy controls allow users to anonymize identities, and initial support is provided for running
smart contracts inside memory spaces encrypted and protected by Intel SGX.
\end{itemize}

Corda follows a general philosophy of reusing existing proven software systems and infrastructure where possible.
Comparisons with Bitcoin and Ethereum will be provided throughout.

\newpage

\section{Overview}

Corda is a platform for the writing and execution of ``CorDapps'': applications that extend the global database with new capabilities.
Such apps define new data types, new inter-node protocol flows and the so-called ``smart contracts'' that determine
allowed changes.

What is a smart contract? That depends on the model of computation we are talking about. There are two competing
computational models used in decentralised databases: the virtual computer model and the UTXO model. The virtual
computer model is used by Ethereum\cite{Ethereum} and Hyperledger Fabric. It models the database as the in-memory state of a
global computer with a single thread of execution determined by the block chain. In the UTXO model, as used in
Bitcoin, the database is a set of immutable rows keyed by \texttt{(hash:output index)}. Transactions define
outputs that append new rows and inputs which consume existing rows. The term ``smart contract'' has a different
meaning in each model. A deeper discussion of the tradeoffs and terminology in the different approaches can
be found in the Corda introductory paper\cite{CordaIntro}.

We use the UTXO model and as a result our transactions are structurally similar to Bitcoin transactions: they have
inputs, outputs and signatures. Unlike Bitcoin, Corda database rows can contain arbitrary data, not just a value field.
Because the data consumed and added by transactions is not necessarily a set of key/value pairs, we don't talk about rows
but rather \emph{states}. Like Bitcoin, Corda states are associated with bytecode programs that must accept a transaction
for it to be valid, but unlike Bitcoin, a transaction must satisfy the programs for both the input and output states
at once. \emph{Issuance transactions} may append new states to the database without consuming any existing states but
unlike in Bitcoin these transactions are not special and may be created at any time, by anyone.

In contrast to both Bitcoin and Ethereum, Corda does not order transactions using a block chain and by implication does
not use miners or proof-of-work. Instead each state points to a \emph{notary}, which is a service that guarantees it
will sign a transaction only if all the input states are un-consumed. A transaction is not allowed to consume states
controlled by multiple notaries and thus there is never any need for two-phase commit between notaries. If a combination of
states would cross notaries then a special transaction type is used to move them onto a single notary first. See~\cref{sec:notaries}
for more information.

The Corda transaction format has various other features which are described in later sections.

\section{The peer to peer network}

\subsection{Network overview}
A Corda network consists of the following components:

\begin{itemize}
\item Nodes, operated by \emph{parties}, communicating using AMQP/1.0 over TLS.
\item An \emph{doorman} service, that grants parties permission to use the network by provisioning identity certificates.
\item A network map service that publishes information about how to connect to nodes on the network.
\item One or more notary services. A notary may itself be distributed over a coalition of different parties.
\item Zero or more oracle services. An oracle is a well known service that signs transactions if they state a fact
and that fact is considered to be true. They may also optionally also provide the facts. This is how the ledger can be
connected to the real world, despite being fully deterministic.
\end{itemize}

% TODO: Add section on zones and network parameters

A purely in-memory implementation of the messaging subsystem is provided which can inject simulated latency between
nodes and visualise communications between them. This can be useful for debugging, testing and educational purposes.

Oracles and notaries are covered in later sections.

\subsection{Identity and the permissioning service}

Unlike Bitcoin and Ethereum, Corda is designed for semi-private networks in which admission requires obtaining an
identity signed by a root authority. This assumption is pervasive -- the flow API provides messaging in terms of identities,
with routing and delivery to underlying nodes being handled automatically. There is no global broadcast at any point.

This `identity' does not have to be a legal or true identity. In the same way that an email address is a globally
unique pseudonym that is ultimately rooted by the top of the DNS hierarchy, so too can a Corda network work with
arbitrary self-selected usernames. The permissioning service can implement any policy it likes as long as the
identities it signs are globally unique. Thus an entirely anonymous Corda network is possible if a suitable
IP obfuscation system like Tor\cite{Dingledine:2004:TSO:1251375.1251396} is also used.

Whilst simple string identities are likely sufficient for some networks, industrial deployments typically require some
level of identity verification, as well as differentiation between different legal entities, branches and desks
that may share the same brand name. Corda reuses the standard PKIX infrastructure for connecting public keys to
identities and thus names are actually X.500 names. Because legal names are unique only within a jurisdiction, the
additional structure X.500 provides is useful  to differentiate between entities with the same name. For example
there are at least five different companies called \emph{American Bank} and in the past there may have been more
than 40 independent banks with that name.

More complex notions of identity that may attest to many time-varying attributes are not handled at this layer of the
system: the base identity is always just an X.500 name. Note that even though messaging is always identified, ledger data
itself may contain only anonymised public keys.

\subsection{The network map}

Every network requires a network map. This is similar to Tor's concept of \emph{directory authorities}. The network
map service publishes information about each node such as the set of IP addresses it listens on (multiple IP
addresses are supported for failover and load balancing purposes), the version of the protocol it speaks, and which
identity certificates it hosts. Each data structure describing a node is signed by the identity keys it claims to
host. The network map service is therefore not trusted to specify node data correctly, only to distribute it.

The network map abstracts the underlying network locations of the nodes to more useful business concepts like
identities and services. Domain names for the underlying IP addresses may be helpful for debugging but are not
required. User interfaces and APIs always work in terms of identities -- there is thus no equivalent to Bitcoin's
notion of an address (hashed public key), and user-facing applications rely on auto-completion and search rather
than QRcodes to identify a counterparty.

It is possible to subscribe to network map changes and registering with the map is the first thing a node does at
startup.

The map is a set of files that may be cached and distributed via HTTP based content delivery networks. The
underlying map infrastructure is therefore not required to be highly available: if the map service becomes
unreachable nodes may not join the network or change IP addresses, but otherwise things continue as normal.

\subsection{Message delivery}

The network is structurally similar to the email network. Nodes are expected to be long lived but may depart
temporarily due to crashes, connectivity interruptions or maintenance. Messages are written to disk
and delivery is retried until the remote node has acknowledged a message, at which point it is expected to have
either reliably stored the message or processed it completely. Connections between nodes are built and torn down as
needed: there is no assumption of constant connectivity. An ideal network would be entirely flat with high quality
connectivity between all nodes, but Corda recognises that this is not always compatible with common network
setups and thus the message routing component of a node can be separated from the rest and run outside the firewall.
Being outside the firewall or in the firewall's `de-militarised zone' (DMZ) is required to ensure that nodes can
connect to anyone on the network, and be connected to in turn. In this way a node can be split into multiple
sub-services that do not have duplex connectivity yet can still take part in the network as first class citizens.

The reference implementation provides this functionality using the Apache Artemis message broker, through which it
obtains journalling, load balancing, flow control, high availability clustering, streaming of messages too large to fit
in RAM and many other useful features. The network uses the \emph{AMQP/1.0}\cite{AMQP} protocol which is a widely
implemented binary messaging standard, combined with TLS to secure messages in transit and authenticate the endpoints.

\subsection{Serialization}\label{subsec:serialization}

All messages are encoded using an extended form of the AMQP/1.0 binary format (\emph{Advanced Message Queue
Protocol}\cite{AMQP}). Each message has a UUID set in an AMQP header which is used as a deduplication key, thus
accidentally redelivered messages will be ignored.

Messages may also have an associated organising 64-bit \emph{session ID}. Note that this is distinct from the AMQP
notion of a session. Sessions can be long lived and persist across node restarts and network outages. They exist in
order to group messages that are part of a \emph{flow}, described in more detail below.

Corda uses AMQP and extends it with more advanced types and embedded binary schemas, such that all messages are self
describing. Because ledger data typically represents business agreements and data, it may persist for years and
survive many upgrades and infrastructure changes. We require that data is always interpretable in strongly typed
form, even if that data has been stored to a context-free location like a file, or the clipboard.

Although based on AMQP, Corda's type system is fundamentally the Java type system. Java types are mapped to AMQP/1.0
types whenever practical, but ledger data will frequently contain business types that the AMQP type system does not
define. Fortunately, AMQP is extensible and supports standard concepts like polymorphism and interfaces, so it is
straightforward to define a natural Java mapping. Type schemas are hashed to form a compact `fingerprint' that
identifies the type, which allows types to be connected to the embedded binary schemas that describe them and which
are useful for caching. The AMQP type system and schema language supports a form of annotations that we map to Java
annotations.

Object serialization frameworks must always consider security. Corda requires all types that may appear in
serialized streams to mark themselves as safe for deserialization, and objects are only created via their
constructors. Thus any data invariants that are enforced by constructors or setter methods are also enforced for
deserialized data. Additionally, requests to deserialize an object specify the expected types. These two mechanisms
block gadget-based attacks\cite{DeserialisingPickles}. Such attacks frequently affect any form of data
deserialization regardless of format, for example, they have been found not only in Java object serialization
frameworks but also JSON and XML parsers. They occur when a deserialization framework may instantiate too large a
space of types which were not written with malicious input in mind.

The serialization framework supports advanced forms of data evolution. When a stream is deserialized Corda attempts
to map it to the named Java classes. If those classes don't exactly match, a process called `evolution' is
triggered, which automatically maps the data as smoothly as possible. For example, deserializing an old object will
attempt to use a constructor that matches the serialized schema, allowing default values in new code to fill in the
gaps. When old code reads data from the future, new fields will be discarded if safe to do so. Various forms of type
adaptation are supported, and type-safe enums can have unknown values mapped to a default enum value as well.

If no suitable class is found at all, the framework performs \emph{class synthesis}. The embedded schema data will
be used to generate the bytecode for a suitable holder type and load it into the JVM on the fly. These new classes
will then be instantiated to hold the deserialized data. The new classes will implement any interfaces the schema is
specified as supporting if those interfaces are found on the Java classpath. In this way the framework supports a
form of generic programming. Tools can work with serialized data without having a copy of the app that generated it.
The returned objects can be accessed either using reflection, or a simple interface that automates accessing
properties by name and is just a friendlier way to access fields reflectively. Creating genuine object graphs like
this is superior to the typical approach of defining a format specific generic data holder type (XML's DOM
\texttt{Element}, \texttt{JSONObject} etc) because there is already a large ecosystem of tools and technologies that
know how to work with objects via reflection. Synthesised object graphs can be fed straight into JSON or YaML
serializers to get back text, inserted into a scripting engine for usage with dynamic languages like JavaScript or
Python, fed to JPA for database persistence and query or a Bean Validation engine for integrity checking, or even
used to automatically generate GUIs using a toolkit like MetaWidget\cite{MetaWidget} or
ReflectionUI\cite{ReflectionUI}.

\section{Flow framework}\label{sec:flows}

\subsection{Overview}

It is common in decentralised ledger systems for complex multi-party protocols to be needed. The Bitcoin payment channel
protocol\cite{PaymentChannels} involves two parties putting money into a multi-signature pot, then iterating with your
counterparty a shared transaction that spends that pot, with extra transactions used for the case where one party or the
other fails to terminate properly. Such protocols typically involve reliable private message passing, checkpointing to
disk, signing of transactions, interaction with the p2p network, reporting progress to the user, maintaining a complex
state machine with timeouts and error cases, and possibly interaction with internal systems on either side. All
this can become quite involved. The implementation of payment channels in the \texttt{bitcoinj} library is approximately
9000 lines of Java, very little of which involves cryptography.

As another example, the core Bitcoin protocol only allows you to append transactions to the ledger. Transmitting other
information that might be useful such as a text message, refund address, identity information and so on is not supported
and must be handled in some other way -- typically by wrapping the raw ledger transaction bytes in a larger message that
adds the desired metadata and giving responsibility for broadcasting the embedded transaction to the recipient, as in
Bitcoin's BIP 70\cite{BIP70}.

In Corda transaction data is not globally broadcast. Instead it is transmitted to the relevant parties only when they
need to see it. Moreover even quite simple use cases -- like sending cash -- may involve a multi-step negotiation between
counterparties and the involvement of a third party such as a notary. Additional information that isn't put into the
ledger is considered essential, as opposed to nice-to-have. Thus unlike traditional block chain systems in which the primary
form of communication is global broadcast, in Corda \emph{all} communication takes the form of small multi-party sub-protocols
called flows.

The flow framework presents a programming model that looks to the developer as if they have the ability to run millions
of long lived threads which can survive node restarts. APIs are provided to send and receive
serialized object graphs to and from other identities on the network, embed sub-flows, handle version evolution and
report progress to observers. In this way business logic can be expressed at a very high level, with the details of
making it reliable and efficient abstracted away. This is achieved with the following components.

\paragraph{Just-in-time state machine compiler.}Code that is written in a blocking manner typically cannot be stopped
and transparently restarted later. The first time a flow's \texttt{call} method is invoked a bytecode-to-bytecode
transformation occurs that rewrites the classes into a form that implements a resumable state machine. These state
machines are sometimes called coroutines, and the transformation engine Corda uses (Quasar) is capable of rewriting
code arbitrarily deep in the stack on the fly. The developer may thus break his or her logic into multiple methods and
classes, use loops, and generally structure their program as if it were executing in a single blocking thread. There's only a
small list of things they should not do: sleeping, directly accessing the network APIs, or doing other tasks that might
block outside of the framework.

\paragraph{Transparent checkpointing.}When a flow wishes to wait for a message from another party (or input from a
human being) the underlying stack frames are suspended onto the heap, then crawled and serialized into the node's
underlying relational database (however, the AMQP framework isn't used in this case). The written objects are prefixed
with small schema definitions that allow some measure of portability across changes to the layout of objects,
although portability across changes to the stack layout is left for future work. Flows are resumed and suspended on
demand, meaning it is feasible to have far more flows active at once than would fit in memory. The checkpointing process
is atomic with respect to changes to the database and acknowledgement of network messages.

\paragraph{Identity to IP address mapping.}Flows are written in terms of identities. The framework takes care of routing
messages to the right IP address for a given identity, following movements that may take place whilst the flow is active
and handling load balancing for multi-homed parties as appropriate.

\paragraph{A library of subflows.}Flows can invoke sub-flows, and a library of flows is provided to automate common tasks
like notarising a transaction or atomically swapping ownership of two assets.

\paragraph{Progress reporting.}Flows can provide a progress tracker that indicates which step they are up to. Steps can
have human-meaningful labels, along with other tagged data like a progress bar. Progress trackers are hierarchical and
steps can have sub-trackers for invoked sub-flows.

\paragraph{Flow hospital.}Flows can pause if they throw exceptions or explicitly request human assistance. A flow that
has stopped appears in the \emph{flow hospital} where the node's administrator may decide to kill the flow or provide it
with a solution. Some flows that end up in the hospital will be retried automatically by the node itself, for example
in case of database deadlocks that require a retry. The ability to request manual solutions is useful for cases
where the other side isn't sure why you are contacting them, for example, the specified reason for sending a payment
is not recognised, or when the asset used for a payment is not considered acceptable.

Flows are identified using Java class names i.e. reverse DNS notation, and several are defined by the base protocol.
Note that the framework is not required to implement the wire protocols, it is just a development aid.

% TODO: Revisit this diagram once it matches the text more closely.
%\begin{figure}[H]
%\includegraphics[scale=0.16, center]{trading-flow}
%\caption{A diagram showing the two party trading flow with notarisation}
%\end{figure}

\subsection{Data visibility and dependency resolution}

When a transaction is presented to a node as part of a flow it may need to be checked. Simply sending you
a message saying that I am paying you \pounds1000 is only useful if you are sure I own the money I'm using to pay you.
Checking transaction validity is the responsibility of the \texttt{ResolveTransactions} flow. This flow performs
a breadth-first search over the transaction graph, downloading any missing transactions into local storage from
the counterparty, and validating them. The search bottoms out at the issuance transactions. A transaction is not
considered valid if any of its transitive dependencies are invalid.

It is required that a node be able to present the entire dependency graph for a transaction it is asking another
node to accept. Thus there is never any confusion about where to find transaction data and there is never any
need to reach out to dozens of nodes which may or may not be currently available. Because transactions are
always communicated inside a flow, and flows embed the resolution flow, the necessary dependencies are fetched
and checked automatically from the correct peer. Transactions propagate around the network lazily and there is
no need for distributed hash tables.

This approach has several consequences. One is that transactions that move highly liquid assets like cash may
end up becoming a part of a very long chain of transactions. The act of resolving the tip of such a graph can
involve many round-trips and thus take some time to fully complete. How quickly a Corda network can send payments
is thus difficult to characterise: it depends heavily on usage and distance between nodes. Whilst nodes could
pre-push transactions in anticipation of them being fetched anyway, such optimisations are left for future work.

Whilst this system is simpler than creating rigid data partitions and clearly provides better privacy than global
broadcast, in the absence of additional privacy measures it is nonetheless still difficult to reason about who
may get to see transaction data. This uncertainty is mitigated by several factors.

\paragraph{Small-subgraph transactions.}Some uses of the ledger do not involve widely circulated asset states.
For example, two institutions that wish to keep their view of a particular deal synchronised but who are making
related payments off-ledger may use transactions that never go outside the involved parties. A discussion of
on-ledger vs off-ledger cash can be found in a later section.

\paragraph{Transaction privacy techniques.}Corda supports a variety of transaction data hiding techniques. For
example, public keys can be randomised to make it difficult to link transactions to an identity. ``Tear-offs'' (\cref{sec:tear-offs})
allow some parts of a transaction to be presented without the others. In future versions of the system secure hardware
and/or zero knowledge proofs could be used to convince a party of the validity of a transaction without revealing the
underlying data.

\paragraph{State re-issuance.}In cases where a state represents an asset that is backed by a particular issuer,
and the issuer is trusted to behave atomically even when the ledger isn't forcing atomicity, the state can
simply be `exited' from the ledger and then re-issued. Because there are no links between the exit and reissue
transactions this shortens the chain. In practice most issuers of highly liquid assets are already trusted with
far more sensitive tasks than reliably issuing pairs of signed data structures, so this approach is unlikely to
be an issue.

\section{Data model}

\subsection{Transaction structure}\label{subsec:transaction-structure}

States are the atomic unit of information in Corda. They are never altered: they are either current (`unspent') or
consumed (`spent') and hence no longer valid.  Transactions read zero or more states (inputs), consume zero or more of
the read states, and create zero or more new states (outputs). Because states cannot exist outside of the transactions
that created them, any state whether consumed or not can be identified by the identifier of the creating transaction
and the index of the state in the outputs list.

A basic need is to represent pointers to data on the ledger. A \texttt{StateRef} type models the combination of a
transaction identifier and an output index. StateRefs can identify any piece of data on the ledger at any point in its
history in a compact, unified form. The \texttt{StatePointer} type unifies a standard JVM memory reference with its
cryptographic ledger counterpart. There are two kinds of pointer: static and linear. A static pointer is simply a
wrapped \texttt{StateRef} which can be easily resolved to the pointed-to state if it's available in the vault. A
linear pointer contains a UUID (universally unique identifier, a 128-bit random number) that identifies a chain of
\emph{linear states}. Linear states copy the UUID from input to output, thus allowing you to talk about the latest
version of a piece of data independent of its hash-based ledger coordinates.

Transactions consist of the following components:

\begin{labeling}{Input references}
\item [Consuming input references.] These are \texttt{(hash, output index)} pairs that point to the states a
transaction is consuming.
\item [Output states.] Each state specifies the notary for the new state, the contract(s) that define its allowed
transition functions and finally the data itself.
\item [Non-consuming input references.] These are also \texttt{(hash, output index)} pairs, however these `reference
states' are not consumed by the act of referencing them. Reference states are useful for importing data that gives
context to other states but which is only changed from time to time. Note that the pointed to state must be unconsumed
at the time the transaction is notarised: if it's been consumed itself as part of a different transaction, the referencing
transaction will not be notarised. In this way, non-consuming input references can help prevent the execution of
transactions that rely on out-of-date reference data.
\item [Attachments.] Transactions specify an ordered list of zip file hashes. Each zip file may contain
code, data or supporting documentation for the transaction. Contract code has access to the contents
of the attachments when checking the transaction for validity. Attachments have no concept of `spentness' and are useful
for things like holiday calendars, timezone data, bytecode that defines the contract logic and state objects, and so on.
\item [Commands.] There may be multiple allowed output states from any given input state. For instance
an asset can be moved to a new owner on the ledger, or issued, or exited from the ledger if the asset has been
redeemed by the owner and no longer needs to be tracked. A command is essentially a parameter to the contract
that specifies more information than is obtainable from examination of the states by themselves (e.g. data from an oracle
service). Each command has an associated list of public keys. Like states, commands are object graphs. Commands therefore
define what a transaction \emph{does} in a conveniently accessible form.
\item [Signatures.] The set of required signatures is equal to the union of the commands' public keys. Signatures can use
a variety of cipher suites - Corda implements cryptographic agility.
\item [Type.] Transactions can either be normal, notary-changing or explicit upgrades. The validation rules for each are
different.
\item [Timestamp.] When present, a timestamp defines a time range in which the transaction is considered to
have occurred. This is discussed in more detail below.
% \item [Network parameters.] Specifies the hash and epoch of the network parameters that were in force at the time the
% transaction was notarised. See \cref{sec:network-params} for more details.
% \item [Summaries] Textual summaries of what the transaction does, checked by the involved smart contracts. This field
% is useful for secure signing devices (see \cref{sec:secure-signing-devices}).
\end{labeling}

% TODO: This description ignores the participants field in states, because it probably needs a rethink.
% TODO: Summaries aren't implemented.

The platform provides a \texttt{TransactionBuilder} class which, amongst many other features, automatically searches
the object graph of each state and command to locate linear pointers, resolve them to the latest known state and add
that state as a non-consumed input, then searches the resolved state recursively. Note that the `latest' version is determined relative to an individual node's
viewpoint, thus, it may not be truly the latest version at the time the transaction is built. The state's notary
cluster will reject the transaction if this occurs, at which point the node may take some action to discover the
latest version of the state and try again.

Transactions are identified by the root of a Merkle tree computed over the components. The transaction format is
structured so that it's possible to deserialize some components but not others: a \emph{filtered transaction} is one
in which only some components are retained (e.g. the inputs) and a Merkle branch is provided that proves the
inclusion of those components in the original full transaction. We say these components have been `torn off'. This
feature is particularly useful for keeping data private from notaries and oracles. See~\cref{sec:tear-offs}.

Signatures are appended to the end of a transaction thus signature malleability as seen in the Bitcoin protocol is
not a problem. There is never a need to identify a transaction with its accompanying signatures by hash. Signatures
can be both checked and generated in parallel, and they are not directly exposed to contract code. Instead contracts
check that the set of public keys specified by a command is appropriate, knowing that the transaction will not be
valid unless every key listed in every command has a matching signature. Public key structures are themselves
opaque. In this way high performance through parallelism is possible and algorithmic agility is retained. New
signature algorithms can be deployed without adjusting the code of the smart contracts themselves.

This transaction structure is fairly complex relative to competing systems. The Corda data model is designed for
richness, evolution over time and high performance. The cost of this is that transactions have more components than
in simpler systems.

\begin{figure}[H]
\includegraphics[width=\textwidth]{cash}
\caption{An example of a cash issuance transaction}
\end{figure}

\paragraph{Example.}In the diagram above, we see an example of a cash issuance transaction. The transaction (shown lower
left) contains zero inputs and one output, a newly issued cash state. The cash state (shown expanded top right) contains
several important pieces of information: 1) details about the cash that has been issued -- amount, currency, issuer,
owner and so forth, 2) the contract code whose verify() function will be responsible for verifying this issuance
transaction and also any transaction which seeks to consume this state in the future, 3) a hash of a document which may
contain overarching legal prose to ground the behaviour of this state and its contract code in a governing legal
context.

The transaction also contains a command, which specifies that the intent of this transaction is to issue cash and the
command specifies a public key. The cash state's verify function is responsible for checking that the public key(s)
specified on the command(s) are those of the parties whose signatures would be required to make this transaction valid.
In this case, it means that the verify() function must check that the command has specified a key corresponding to the
identity of the issuer of the cash state. The Corda framework is responsible for checking that the transaction has been
signed by all keys listed by all commands in the transaction. In this way, a verify() function only needs to ensure that
all parties who need to sign the transaction are specified in commands, with the framework responsible for ensuring that
the transaction has been signed by all parties listed in all commands.

\subsection{Composite keys}\label{sec:composite-keys}

The term ``public key'' in the description above actually refers to a \emph{composite key}. Composite keys are trees in
which leaves are regular cryptographic public keys with an accompanying algorithm identifiers. Nodes in the tree specify
both the weights of each child and a threshold weight that must be met. The validity of a set of signatures can be
determined by walking the tree bottom-up, summing the weights of the keys that have a valid signature and comparing
against the threshold. By using weights and thresholds a variety of conditions can be encoded, including boolean
formulas with AND and OR.

\begin{figure}[H]
\includegraphics[width=\textwidth]{composite-keys}
\caption{Examples of composite keys}
\end{figure}

Composite keys are useful in multiple scenarios. For example, assets can be placed under the control of a 2-of-2
composite key where one leaf key is owned by a user, and the other by an independent risk analysis system. The
risk analysis system refuses to sign if the transaction seems suspicious, like if too much value has been
transferred in too short a time window. Another example involves encoding corporate structures into the key,
allowing a CFO to sign a large transaction alone but his subordinates are required to work together.

Composite keys are also useful for byzantine fault tolerant notaries. Each participant in a distributed notary is
represented by a leaf, and the threshold is set such that some participants can be offline or refusing to sign
yet the signature of the group is still valid.

Whilst there are threshold signature schemes in the literature that allow composite keys and signatures to be produced
mathematically, we choose the less space efficient explicit form in order to allow a mixture of keys using different
algorithms. In this way old algorithms can be phased out and new algorithms phased in without requiring all
participants in a group to upgrade simultaneously.

\subsection{Time handling}\label{sec:timestamps}

Transaction timestamps specify a \texttt{[start, end]} time window within which the transaction is asserted to have
occurred. Timestamps are expressed as windows because in a distributed system there is no true time, only a large number
of desynchronised clocks. This is not only implied by the laws of physics but also by the nature of shared transactions
- especially if the signing of a transaction requires multiple human authorisations, the process of constructing
a joint transaction could take hours or even days.

It is important to note that the purpose of a transaction timestamp is to communicate the transaction's position
on the timeline to the smart contract code for the enforcement of contractual logic. Whilst such timestamps may
also be used for other purposes, such as regulatory reporting or ordering of events in a user interface, there is
no requirement to use them like that and locally observed timestamps may sometimes be preferable even if they will
not exactly match the time observed by other parties. Alternatively if a precise point on the timeline is required
and it must also be agreed by multiple parties, the midpoint of the time window may be used by convention. Even
though this may not precisely align to any particular action (like a keystroke or verbal agreement) it is often
useful nonetheless.

Timestamp windows may be open ended in order to communicate that the transaction occurred before a certain
time or after a certain time, but how much before or after is unimportant. This can be used in a similar
way to Bitcoin's \texttt{nLockTime} transaction field, which specifies a \emph{happens-after} constraint.

Timestamps are checked and enforced by notary services. As the participants in a notary service will themselves
not have precisely aligned clocks, whether a transaction is considered valid or not at the moment it is submitted
to a notary may be unpredictable if submission occurs right on a boundary of the given window. However, from the
perspective of all other observers the notary's signature is decisive: if the signature is present, the transaction
is assumed to have occurred within that time.

\paragraph{Reference clocks.}In order to allow for relatively tight time windows to be used when transactions are
fully under the control of a single party, notaries are expected to be synchronised to international atomic time
(TIA). Accurate feeds of this clock can be obtained from GPS satellites and long-wave radio. Note that Corda uses
the Google/Amazon timeline, which is UTC with a leap smear from noon to noon across the leap event, thus each day
always has exactly 86400 seconds.

\paragraph{Timezones.}Business agreements typically specify times in local time zones rather than offsets from
midnight UTC on January 1st 1970, although the latter would be more civilised. Because the Corda type system is the
Java type system, developers can embed \texttt{java.time.ZonedDateTime} in their states to represent a time
specified in a specific time zone. This allows ensure correct handling of daylight savings transitions and timezone
definition changes. Future versions of the platform will allow timezone data files to be attached to transactions,
to make such calculations entirely deterministic.

\subsection{Attachments and contract bytecodes}\label{subsec:attachments-and-contract-bytecodes}

Transactions may have a number of \emph{attachments}, identified by the hash of the file. Attachments are stored
and transmitted separately to transaction data and are fetched by the standard resolution flow only when the
attachment has not previously been seen before.

Attachments are always zip files\cite{ZipFormat}. The files within the zips are collapsed together into a single
logical file system and class path.

Smart contracts in Corda are defined using a restricted form of JVM bytecode as specified in
\emph{``The Java Virtual Machine Specification SE 8 Edition''}\cite{JVM},
with some small differences that are described in a later section. A contract is simply a class that implements
the \texttt{Contract} interface, which in turn exposes a single function called \texttt{verify}. The verify
function is passed a transaction and either throws an exception if the transaction is considered to be invalid,
or returns with no result if the transaction is valid. The set of verify functions to use is the union of the contracts
specified by each state, which are expressed as a class name combined with a \emph{constraint} (see~\cref{sec:contract-constraints}).
Embedding the JVM specification in the Corda specification enables developers to write code in a variety of
languages, use well developed toolchains, and to reuse code already authored in Java or other JVM compatible languages.
A good example of this feature in action is the ability to embed the ISDA Common Domain Model directly into CorDapps.
The CDM is a large collection of types mapped to Java classes that model derivatives trading in a standardised way.
It is common for industry groups to define such domain models and for them to have a Java mapping.

Current versions of the platform only execute attachments that have been previously installed (and thus
whitelisted), or attachments that are signed by the same signer as a previously installed attachment. Thus
nodes may fail to reach consensus on long transaction chains that involve apps your counterparty has not seen.
Future versions of the platform will run contract bytecode inside a deterministic JVM. See~\cref{sec:djvm}.

The Java standards also specify a comprehensive type system for expressing common business data. Time and calendar
handling is provided by an implementation of the JSR 310 specification, decimal calculations can be performed either
using portable (`\texttt{strictfp}') floating point arithmetic or the provided bignum library, and so on. These
libraries have been carefully engineered by the business Java community over a period of many years and it makes
sense to build on this investment.

Contract bytecode also defines the states themselves, which may be directed acyclic object graphs. States may label
their properties with a small set of standardised annotations. These can be useful for controlling how states are
serialized to JSON and XML (using JSR 367 and JSR 222 respectively), for expressing static validation constraints
(JSR 349) and for controlling how states are inserted into relational databases (JSR 338). This feature is discussed later.
Future versions of the platform may additionally support cyclic object graphs.

\paragraph{Data files.}Attachments may also contain data files that support the contract code. These may be in the same zip as the
bytecode files, or in a different zip that must be provided for the transaction to be valid. Examples of such
data files might include currency definitions, timezone data and public holiday calendars. Any public data may
be referenced in this way. Attachments are intended for data on the ledger that many parties may wish to reuse
over and over again. Data files are accessed by contract code using the same APIs as any file on the classpath
would be accessed. The platform imposes some restrictions on what kinds of data can be included in attachments
along with size limits, to avoid people placing inappropriate files on the global ledger (videos, PowerPoints etc).

Note that the creator of a transaction gets to choose which files are attached. Therefore, it is typical that
states place constraints on the data they're willing to accept. These mechanisms are discussed in~\cref{sec:contract-constraints}.

\paragraph{Signing.}Attachments may be signed using the JAR signing standard. No particular certificate is necessary
for this: Corda accepts self signed certificates for JARs. The signatures are useful for two purposes. Firstly, it
allows states to express that they can be satisfied by any attachment signed by a particular provider. This allows
on-ledger code to be upgraded over time. And secondly, signed JARs may provide classes in `\emph{claimed packages}',
which are discussed below.

\subsection{Contract constraints}\label{sec:contract-constraints}

In Bitcoin contract logic is embedded inside every transaction. Programs are small and data is inlined into the
bytecode, so upgrading code that's been added to the ledger is neither possible nor necessary. There's no need for a
mechanism to tie code and data together. In Corda contract logic may be far more complex. It will usually reflect a
changing business world which means it may need to be upgraded from time to time.

The easiest way of tying states to the contract code that defines them is by hash. This is equivalent to other
ledger platforms and is referred to as an \emph{hash constraint}. They work well for very simple and stable
programs, but more complicated contracts may need to be upgraded. In this case it may be preferable for states to
refer to contracts by the identity of the signer (a \emph{signature constraint}). Because contracts are stored in
zip files, and because a Java Archive (JAR) file is just a zip with some extra files inside, it is possible to use
the standard JAR signing infrastructure to identify the source of contract code. Simple constraints such as ``any
contract of this name signed by these keys'' allow for some upgrade flexibility, at the cost of increased exposure
to rogue contract developers. Requiring combinations of signatures helps reduce the risk of a rogue or hacked
developer publishing a bad contract version, at the cost of increased difficulty in releasing new versions. State
creators may also specify third parties they wish to review contract code. Regardless of which set of tradeoffs is
chosen, the framework can accommodate them.

A contract constraint may use a composite key of the type described in~\cref{sec:composite-keys}. The standard JAR
signing protocol allows for multiple signatures from different private keys, thus being able to satisfy composite
keys. The allowed signing algorithms are \texttt{SHA256withRSA} and \texttt{SHA256withECDSA}. Note that the
cryptographic algorithms used for code signing may not always be the same as those used for transaction signing, as
for code signing we place initial focus on being able to re-use the infrastructure.

\subsection{Precise naming}\label{subsec:precise-naming}

In any system that combines typed data with potentially malicious adversaries, it's important to always ensure
names are not allowed to become ambiguous or mixed up. Corda achieves this via a combination of different
features.

\paragraph{No overlap rule.} Within a transaction attachments form a Java classpath. Class names are resolved
by locating the defining class file within the set of attachments and loading them via the deterministic JVM.
Unfortunately, out of the box Java allows different JAR files to define the same class name. Whichever JAR
happens to come first on the classpath is the one that gets used, but conventionally a classpath is not meant
to have an important ordering. This problem is a frequent source of confusion and bugs in Java software,
especially when different versions of the same module are combined into one program. On the ledger an adversary
can craft a malicious transaction that attempts to trick a node or application into thinking it does one thing
whilst actually doing another. To prevent attackers from building deliberate classpath conflicts to change the
behaviour of code, a transaction in which two file paths overlap between attachments is invalid. A small number
of files that are expected to overlap normally, such as files in the \texttt{META-INF} directory, are excluded.

\paragraph{Package namespace ownership.} Corda allows parts of the Java package namespace to be reserved for
particular developers, identified by a public key (which may or may not be an identity on the node's zone).
Any JAR that exports a class in an owned package namespace but which is not signed by the owning key is
considered to be invalid. Reserving a package namespace is optional but can simplify the data model and make
applications more secure.

The reason for this is related to a mismatch between the way the ledger names code and the way programming
languages do. In the distributed ledger world a bundle of code is referenced by hash or signing key, but in
source code English-like module names are used. In the Java ecosystem these names are broken into components
separated by dots, and there's a strong convention that names are chosen to start with the reversed domain
name of the developer's website. For example a developer who works for MegaCorp may use
\texttt{com.megacorp.superproduct.submodule} as a prefix for the names used in that specific product and
submodule.

However this is only a convention. Nothing prevents anyone from publishing code that uses MegaCorp's package
namespace. Normally this isn't a problem as developers learn the correct names via some secure means, like
browsing an encrypted website of good reputation. But on a distributed ledger data can be encountered which
was crafted by a malicious adversary, usually a trading partner who hasn't been extensively verified or who
has been compromised. Such an adversary could build a transaction with a custom state and attachment that
defined classes with the same name as used by a real app. Whilst the core ledger can differentiate between the
two applications, if data is serialized or otherwise exposed via APIs that rely on ordinary types and class
names the hash or signer of the original attachment can easily get lost.

For example, if a state is serialized to JSON at any point then \emph{any} type that has the same shape can
appear legitimate. In Corda serialization types are ultimately identified by class name, as is true for all
other forms of serialization. Thus deserializing data and assuming the data represents a state only reachable
by the contract logic would be risky if the developer forgot to check that the original smart contract was the
intended contract and not one violating the naming convention.

By enforcing the Java naming convention cryptographically and elevating it to the status of a consensus rule,
developers can assume that a \texttt{com.megacorp.superproduct.DealState} type always obeys the rules enforced
by the smart contract published by that specific company. They cannot get confused by a mismatch between the
human readable self-assigned name and the cryptographic but non-human readable hash or key based name the
ledger really uses.

% TODO: Discuss confidential identities.
% TODO: Discuss the crypto suites used in Corda.

\subsection{Hard forks, bug fixes and dispute resolution}\label{subsec:hard-forks,-bug-fixes-and-dispute-resolution}

Decentralised ledger systems often differ in their underlying political ideology as well as their technical
choices. The Ethereum project originally promised ``unstoppable apps'' which would implement ``code as law''. After
a prominent smart contract was hacked\cite{TheDAOHack}, an argument took place over whether what had occurred could be described
as a hack at all given the lack of any non-code specification of what the program was meant to do. The disagreement
eventually led to a split in the community.

As Corda contracts are simply zip files, it is easy to include a PDF or other documents describing what a contract
is meant to actually do. A \texttt{@LegalProseReference} annotation is provided which by convention contains a URL
or URI to a specification document. There is no requirement to use this mechanism, and there is no requirement that these
documents have any legal weight. However in financial use cases it's expected that they would be legal contracts that
take precedence over the software implementations in case of disagreement.

It is technically possible to write a contract that cannot be upgraded. If such a contract governed an asset that
existed only on the ledger, like a cryptocurrency, then that would provide an approximation of ``code as law''. We
leave discussion of the wisdom of this concept to political scientists and reddit.

% TODO: Rewrite the section on confidential identities and move it under a new privacy section.

\subsection{Oracles and tear-offs}\label{sec:tear-offs}

It is sometimes convenient to reveal a small part of a transaction to a counterparty in a way that allows them to
both check and create signatures over the entire transaction. One typical use case for this is an \emph{oracle},
defined as a network service that is trusted to sign transactions containing statements about the world outside the
ledger only if the statements are true. Another use case is to outsource signing to small devices that can't or
won't process the entire transaction, which can potentially get very large for multi-party transactions. To make
this safe additional infrastructure is required, described in~\cref{sec:secure-signing-devices}.

Here are some example statements an oracle might check:

\begin{itemize}
\item The price of a stock at a particular moment was X.
\item An agreed upon interest rate at a particular moment was Y.
\item If a specific organisation has declared bankruptcy.
\item Weather conditions in a particular place at a particular time.
\end{itemize}

It is worth asking why a smart contract cannot simply fetch this information from some internet server itself: why
do we insist on this notion of an oracle. The reason is that all calculations on the ledger must be deterministic.
Everyone must be able to check the validity of a transaction and arrive at exactly the same answer, at any time (including years into the future),
on any kind of computer. If a smart contract could do things like read the system clock or fetch arbitrary web pages
then it would be possible for some computers to conclude a transaction was valid, whilst others concluded it was
not (e.g. if the remote server had gone offline). Solving this problem means all the data needed to check the
transaction must be in the ledger, which in turn implies that we must accept the point of view of some specific
observer. That way there can be no disagreement about what happened.

One way to implement oracles would be to have them sign a small data structure which is then embedded somewhere
in a transaction (in a state or command). We take a different approach in which oracles sign the entire transaction,
and data the oracle doesn't need to see is ``torn off'' before the transaction is sent. This is done by structuring
the transaction as a Merkle hash tree so that the hash used for the signing operation is the root. By presenting a
counterparty with the data elements that are needed along with the Merkle branches linking them to the root hash,
as seen in the diagrams below, that counterparty can sign the entire transaction whilst only being able to see some of it. Additionally, if the
counterparty needs to be convinced that some third party has already signed the transaction, that is also
straightforward. Typically an oracle will be presented with the Merkle branches for the command or state that
contains the data, and the timestamp field, and nothing else. The resulting signature contains flag bits indicating which
parts of the structure were presented for signing to avoid a single signature covering more than expected.

\begin{figure}[H]
\includegraphics[width=\textwidth]{tearoffs1}
\caption{How the transaction's identifier hash is calculated}
\end{figure}

\begin{figure}[H]
\includegraphics[width=\textwidth]{tearoffs2}
\caption{Construction of a Merkle branch}
\end{figure}

% TODO: The flag bits are unused in the current reference implementation.

There are several reasons to take this more indirect approach. One is to keep a single signature checking
code path. By ensuring there is only one place in a transaction where signatures may be found, algorithmic
agility and parallel/batch verification are easy to implement. When a signature may be found in any arbitrary
location in a transaction's data structures, and where verification may be controlled by the contract code itself (as in Bitcoin),
it becomes harder to maximise signature checking efficiency. As signature checks are often one of the slowest parts
of a block chain system, it is desirable to preserve these capabilities.

Another reason is to provide oracles with a business model. If oracles just signed statements and nothing else then
it would be difficult to run an oracle in which there are only a small number of potential statements, but
determining their truth is very expensive. People could share the signed statements and reuse them in many different
transactions, meaning the cost of issuing the initial signatures would have to be very high, perhaps
unworkably high. Because oracles sign specific transactions, not specific statements, an oracle that is charging
for its services can amortise the cost of determining the truth of a statement over many users who cannot then
share the signature itself (because it covers a one-time-use structure by definition).

A final reason is that by signing transactions, the signature automatically covers the embedded time window,
as discussed in~\cref{sec:timestamps}. This provides a theoretically robust method of anchoring the oracle's
statement into the ledger's timeline.

\subsection{Encumbrances}\label{sec:encumbrances}

Each state in a transaction specifies a contract (boolean function) that is invoked with the entire transaction as input. All contracts must accept
in order for the transaction to be considered valid. Sometimes we would like to compose the behaviours of multiple
different contracts. Consider the notion of a ``time lock'' -- a restriction on a state that prevents it being
modified (e.g. sold) until a certain time. This is a general piece of logic that could apply to many kinds of
assets. Whilst such logic could be implemented in a library and then called from every contract that might want
to benefit from it, that requires all contract authors to think ahead and include the functionality. It would be
better if we could mandate that the time lock logic ran along side the contract that governs the locked state.

Consider an asset that is supposed to remain frozen until a time is reached. Encumbrances allow a state to specify another
state that must be present in any transaction that consumes it. For example, a time lock contract can define a state that
contains the time at which the lock expires, and a simple contract that just compares that time against the transaction
timestamp. The asset state can be included in a spend-to-self transaction that doesn't change the ownership of the asset
but does include a time lock state in the outputs. Now if the asset state is used, the time lock state must also be used, and
that triggers the execution of the time lock contract.

Encumbered states can only point to one encumbrance state, but that state can itself point to another and so on,
resulting in a chain of encumbrances all of which must be satisfied.

% TODO: Diagram for how this is arranged

An encumbrance state must be present in the same transaction as the encumbered state, as states refer to each other
by index alone.

% TODO: Interaction of enumbrances with notary change transactions.

\subsection{Event scheduling}\label{sec:event-scheduling}

State classes may request flows to be started at given times. When a state is considered relevant by the vault and the
implementing CorDapp is installed and whitelisted by the administrator, the node may react to
the passage of time by starting new interactions with other nodes, people, or internal systems. As financial contracts
often have a notion of time in them this feature can be useful for many kinds of state transitions, for example, expiry
of an option contract, management of a default event, re-fixing of an interest rate swap and so on.

To request scheduled events, a state may implement the \texttt{SchedulableState} interface and then return a
request from the \texttt{nextScheduledActivity} function. The state will be queried when it is committed to the
vault and the scheduler will ensure the relevant flow is started at the right time.

\section{Tokens}\label{sec:tokens}

Some basic concepts occur in many kinds of application, regardless of what industry or use case it is for. The
platform provides a comprehensive type system for modelling of \emph{tokens}: abstract countable objects highly
suited to representing value.

Tokens can be used to model agreements with an issuer, like fiat money, securities, derivatives, debts and
other financial instruments. They could also  be used to model any sort of claim on physical resources,
like CPU time, network bandwidth, barrels of oil and so on. Finally, as a special case tokens can be used to
implement cryptocurrencies (this is modelled as a claim on a null issuer).

We define the notion of an \texttt{OwnableState}, implemented as an interface which any state may conform to.
Ownable states are required to have an \texttt{owner} field which is a composite key
(see~\cref{sec:composite-keys}). This is utilised by generic code in the vault (see~\cref{sec:vault}) to manipulate
ownable states.

From \texttt{OwnableState} we derive a \texttt{FungibleState} concept to represent an aggregation in which units
are sufficiently similar to be represented together in a single ledger state. Making that concrete, pound notes are
a fungible asset: regardless of whether you represent \pounds10 as a single \pounds10 note or two notes of \pounds5
each the total value is the same. Other kinds of fungible asset could be barrels of Brent Oil (but not all kinds of
crude oil worldwide, because oil comes in different grades which are not interchangeable), litres of clean water,
kilograms of bananas, units of a stock and so on.

Quantities are represented with an \texttt{Amount<T>} type which defines an integer amount parameterised by some
other type, usually a singleton object. To support tokens that have a fractional part, as some national currencies
do, the ``display token size'' is tracked explicitly. \texttt{Amount<T>} provides operator overloads to allow
addition, subtraction and multiplication with safety checks to prevent different tokens being combined together and
to catch integer overflow/underflow. These conditions normally indicate a programmer error or attack attempt.
Amounts may not be negative as in many critical contexts a negative quantity is undefined and reachable only
through an error condition. Transfers of value are modelled explicitly with an \texttt{AmountTransfer} type that
encodes direction.

\paragraph{Token SDK.}On top of these universal core types, Corda provides a dedicated `token software development
kit' module that  extends the type system with more sophisticated concepts.

\begin{figure}[H]
\includegraphics[width=\textwidth]{state-class-hierarchy}
\caption{Class hierarchy diagram showing the relationships between different state types}
\end{figure}

\texttt{TokenType} refers to a ``type of thing'' as opposed to the vehicle which is used to assign units of a token
to a particular owner. For that we use the \texttt{NonFungibleToken} state for assigning non-fungible tokens to a
holder and the \texttt{FungibleToken} state for assigning amounts of some fungible token to a holder. Because
tokens frequently represent claims on an issuer the \texttt{IssuedTokenType} class links a token type with an
issuing party. Whilst static token types never change, an \texttt{EvolvableTokenType} is an abstract linear state
that contains data defining the rules of the token or reference data related to it. For example a token type
representing a stock may include various metadata about that stock, such as regional identifiers. Token states are
linked to their defining token type states (when evolvable) using linear pointers
(see~\cref{subsec:transaction-structure}). This enables reference data about a token to be evolved such that
everyone always uses the latest version, ensuring a `golden source'. The lack of such global yet evolvable
definitions is a frequent problem in industry. Tokens with an issuer are \emph{not} fungible with each other: two
pools of pound sterling are considered to be separate types of token if they come from different issuers. This is
to avoid commingling and losing track of counterparty risk.

The token SDK provides APIs and flows to do standard tasks for UTXO based ledgers, such as moving tokens between
parties, issuing tokens, updating the definition of an evolvable token and efficient coin selection. This is the
task of selecting a group of states from the vault that add up to a certain value whilst minimising fragmentation,
transaction size and optimising other desirable characteristics. Although the term ``coin selection'' is an
anachronistic holdover from Bitcoin, Corda continues to use it due to the wealth of published literature exploring
algorithms for the task under this name.

Together, this functionality provides Corda's equivalent of the Ethereum ERC-20 standard\cite{ERC20}.

Having defined various kinds of abstract token, the SDK goes on to define (finally!) \texttt{Money} and
\texttt{FiatCurrency} types. Interop with the JSR 354 standard for representing financial amounts is left to future
work.

%\subsection{Market infrastructure}
%
%Trade is the lifeblood of the economy. A distributed ledger needs to provide a vibrant platform on which trading may
%take place. However, the decentralised nature of such a network makes it difficult to build competitive
%market infrastructure on top of it, especially for highly liquid assets like securities. Markets typically provide
%features like a low latency order book, integrated regulatory compliance, price feeds and other things that benefit
%from a central meeting point.
%
%The Corda data model allows for integration of the ledger with existing markets and exchanges. A sell order for
%an asset that exists on-ledger can have a \emph{partially signed transaction} attached to it. A partial
%signature is a signature that allows the signed data to be changed in controlled ways after signing. Partial signatures
%are directly equivalent to Bitcoin's \texttt{SIGHASH} flags and work in the same way -- signatures contain metadata
%describing which parts of the transaction are covered. Normally all of a transaction would be covered, but using this
%metadata it is possible to create a signature that only covers some inputs and outputs, whilst allowing more to be
%added later.
%
%This feature is intended for integration of the ledger with the order books of markets and exchanges. Consider a stock
%exchange. A buy order can be submitted along with a partially signed transaction that signs a cash input state
%and a output state representing some quantity of the stock owned by the buyer. By itself this transaction is invalid,
%as the cash does not appear in the outputs list and there is no input for the stock. A sell order can be combined with
%a mirror-image partially signed transaction that has a stock state as the input and a cash state as the output. When
%the two orders cross on the order book, the exchange itself can take the two partially signed transactions and merge
%them together, creating a valid transaction that it then notarises and distributes to both buyer and seller. In this
%way trading and settlement become atomic, with the ownership of assets on the ledger being synchronised with the view
%of market participants. Note that in this design the distributed ledger itself is \emph{not} a marketplace, and does
%not handle distribution or matching of orders. Rather, it focuses on management of the pre- and post- trade lifecycles.
%
%\paragraph{Central counterparties.}In many markets, central infrastructures such as clearing houses (also known as
%Central Counterparties, or CCPs) and Central Securities Depositories (CSD) have been created. They provide governance,
%rules definition and enforcement, risk management and shared data and processing services. The partial data visibility,
%flexible transaction verification logic and pluggable notary design means Corda could be a particularly good fit for
%future distributed ledger services contemplated by CCPs and CSDs.
%
%% TODO: Partial signatures are not implemented.

\section{Notaries and consensus}\label{sec:notaries}

Corda does not organise time into blocks. This is sometimes considered strange, given that it can be described as a
block chain system or `block chain inspired'. Instead a Corda network has one or more notary services which provide
transaction ordering and timestamping services, thus abstracting the role miners play in other systems into a pluggable
component.

Notaries are expected to be composed of multiple mutually distrusting parties who use a standard consensus algorithm.
Notaries are identified by and sign with composite public keys (\cref{sec:composite-keys})that conceptually follow the
Interledger Crypto-Conditions specification\cite{ILPCC}. Note that whilst it would be conventional to use a BFT
algorithm for a notary service, there is no requirement to do so and in cases where the legal system is sufficient to
ensure protocol compliance a higher performance algorithm like Raft\cite{Ongaro:2014:SUC:2643634.2643666} may be used.
Because multiple notaries can co-exist a single network may provide a single global BFT notary for general use and
region-specific Raft notaries for lower latency trading within a unified regulatory area, for example London or New York.

Notaries accept transactions submitted to them for processing and either return a signature over the transaction, or
a rejection error that states that a double spend has occurred. The presence of a notary signature from the state's
chosen notary indicates transaction finality. An app developer triggers notarisation by invoking the
\texttt{Finality} flow on the transaction once all other necessary signatures have been gathered. Once the finality flow
returns successfully, the transaction can be considered committed to the database.

\subsection{Comparison to Nakamoto block chains}

Bitcoin organises the timeline into a chain of blocks, with each block pointing to a previous block the miner has chosen
to build upon. Blocks also contain a rough timestamp. Miners can choose to try and extend the block chain from any
previous block, but are incentivised to build on the most recently announced block by the fact that other nodes in the
system only recognise a block if it's a part of the chain with the most accumulated proof-of-work. As each block contains
a reward of newly issued bitcoins, an unrecognised block represents a loss and a recognised block typically represents
a profit.

Bitcoin uses proof-of-work because it has a design goal of allowing an unlimited number of identityless parties to join
and leave the network at will, whilst simultaneously making it hard to execute Sybil attacks (attacks in which one party
creates multiple identities to gain undue influence over the network). This is an appropriate design to use for a peer to
peer network formed of volunteers who can't/won't commit to any long term relationships up front, and in which identity
verification is not done. Using proof-of-work then leads naturally to a requirement to quantise the timeline into chunks,
due to the probabilistic nature of searching for a proof. The chunks must then be ordered relative to each other.
The incentive to build on the most recently announced proof of work is in tension with the reality that it takes
time for a proof to circulate around the network. This means it is desirable that proofs are produced at a rate
that is slow enough that very few are circulating at the same time. Given that transactions are likely to be
produced at a higher rate than this, it implies a need for the proofs to consolidate multiple transactions.
Hence the need for blocks.

A Corda network is email-like in the sense that nodes have long term stable identities, of which they can prove ownership
of to others. Sybil attacks are blocked by the network entry process. This allows us to discard proof-of-work along with
its multiple unfortunate downsides:

\begin{itemize}
\item Energy consumption is excessively high for such a simple task, being comparable at the time of writing to the
electricity consumption of an entire city\cite{BitcoinEnergy}. At a time when humanity needs to use less energy
rather than more this is ecologically undesirable.
\item High energy consumption forces concentration of mining power in regions with cheap or free electricity. This results
in unpredictable geopolitical complexities that many users would rather do without.
\item Identityless participants mean all transactions must be broadcast to all network nodes, as there's no reliable
way to know who the miners are. This worsens privacy.
\item The algorithm does not provide finality, only a probabilistic approximation, which is a poor fit for existing
business and legal assumptions.\cite{Swanson}
\item It is theoretically possible for large numbers of miners or even all miners to drop out simultaneously without
any protocol commitments being violated.
\end{itemize}

Once proof-of-work is disposed of there is no longer any need to quantise the timeline into blocks because there is
no longer any need to slow the publication of conflict resolution proposals, and because the parties asserting the
correctness of the ordering are known ahead of time regular signatures are sufficient.

\subsection{Algorithmic agility}

Consensus algorithms are a hot area of research and new algorithms are frequently developed that improve upon the state
of the art. Unlike most distributed ledger systems Corda does not tightly integrate one specific approach. This is not
only to support upgrades as new algorithms are developed, but also to reflect the fact that different tradeoffs may make
sense for different situations and networks.

As a simple example, a notary that uses Raft between nodes that are all within the same city will provide extremely good
performance and latency, at the cost of being more exposed to malicious attacks or errors by whichever node has been elected
leader. In situations where the members making up a distributed notary service are all large, regulated institutions that
are not expected to try and corrupt the ledger in their own favour trading off security to gain performance may make sense.
In other situations where existing legal or trust relationships are less robust, slower but byzantine fault tolerant
algorithms like BFT-SMaRT\cite{Bessani:2014:SMR:2671853.2672428} may be preferable. Alternatively, hardware security features
like Intel SGX\textregistered may be used to convert non-BFT algorithms into a more trusted form using remote attestation and
hardware protection.

Being able to support multiple notaries in the same network has other advantages:

\begin{itemize}
\item It is possible to phase out notaries (i.e. sets of participants) that no longer wish to provide that service by
migrating states.
\item The scalability of the system can be increased by bringing online new notaries that run in parallel. As long as access
to the ledger has some locality (i.e. states aren't constantly being migrated between notaries) this allows for the scalability
limits of common consensus algorithms or node hardware to be worked around.
\item In some but not all cases, regulatory constraints on data propagation can be respected by having jurisdictionally
specific notaries. This would not work well when two jurisdictions have mutually incompatible constraints or for assets that
may frequently travel around the world, but it can work when using the ledger to track the state of deals or other facts that
are inherently region specific.
\item Notaries can compete on their availability and performance.
\item Users can pick between \emph{validating} and \emph{non-validating} notaries. See below.
\item In some models for how these technologies will be adopted, it is possible that issuers of assets will find it
convenient to 'self-notarise' transactions that pertain to assets they have issued and this necessarily requires
support for multiple notaries in the same network. Such a model is likely to be a transitional state, not least
because such a model is inherently limited in the range of operations that can be supported.
\item Separate networks can start independent and be merged together later (see below).
\end{itemize}

\subsection{Validating and non-validating notaries}\label{sec:non-validating-notaries}

Validating notaries resolve and fully check transactions they are asked to deconflict. Thus in the degenerate case of a
network with just a single notary and without the use of any privacy features, they gain full visibility into every
transaction. Non-validating notaries assume transaction validity and do not request transaction data or their
dependencies beyond the list of states consumed. With such a notary it is possible for the ledger to become `wedged', as
anyone who knows the hash and index of a state may consume it without checks. If the cause of the problem is accidental,
the incorrect data can be presented to a non-validating notary to convince it to roll back the commit, but if the error
is malicious then states controlled by such a notary may become permanently corrupted.

It is therefore possible for users to select their preferred point on a privacy/security spectrum for each state individually
depending on how they expect the data to be used. When the states are unlikely to live long or propagate far and the only
entities who will learn their transaction hashes are somewhat trustworthy, the user may select to keep the data from the
notary. For liquid assets a validating notary should always be used to prevent value destruction and theft if the transaction
identifiers leak.

\subsection{Merging networks}

Because there is no single block chain it becomes possible to merge two independent networks together by simply establishing
two-way connectivity between their nodes then configuring each side to trust each other's notaries and certificate authorities.

This ability may seem pointless: isn't the goal of a decentralised ledger to have a single global database for everyone?
It is, but a practical route to reaching this end state is still required. It is often the case that organisations
perceived by consumers as being a single company are in fact many different entities cross-licensing branding, striking
deals with each other and doing internal trades with each other. This sort of setup can occur for regulatory reasons,
tax reasons, due to a history of mergers or just through a sheer masochistic love of paperwork. Very large companies can
therefore experience all the same synchronisation problems a decentralised ledger is intended to fix but purely within
the bounds of that organisation. In this situation the main problem to tackle is not malicious actors but rather
heterogenous IT departments, varying software development practices, unlinked user directories and so on.
Such organisations can benefit from gaining experience with the technology internally and cleaning up their own
internal views of the world before tackling the larger problem of synchronising with the wider world as well.

When merging networks, both sides must trust that each other's notaries have never signed double spends. When merging an
organisation-private network into the global ledger it should be possible to simply rely on incentives to provide
this guarantee: there is no point in a company double spending against itself. However, if more evidence is desired, a
standalone notary could be run against a hardware security module with audit logging enabled. The notary itself would simply
use a private database and run on a single machine, with the logs exported to the people running a global network for
asynchronous post-hoc verification.

\subsection{Guaranteed data distribution}

In any global consensus system the user is faced with the question of whether they have the latest state of the database.
Programmers working with block chains often make the simplifying assumption that because there is no formal map
of miner locations and thus transactions are distributed to miners via broadcast, that they can listen to the
stream of broadcasts and learn if they have the latest data. Alas, nothing stops someone privately providing a
miner who has a known location with a transaction that they agree not to broadcast. The first time the rest of
the network finds out about this transaction is when a block containing it is broadcast. When used to do double
spending fraud this type of attack is known as a Finney Attack\cite{FinneyAttack}. Proof-of-work based systems
rely on aligned incentives to discourage such attacks: to quote the Bitcoin white paper, \blockquote{He ought to
find it more profitable to play by the rules ... than to undermine the system and the validity of his own wealth.}
In practice this approach appears to work well enough most of the time, given that miners typically do not accept
privately submitted transactions.

In a system without global broadcast things are very different: the notary clusters \emph{must} accept transactions
directly and there is no mechanism to ensure that everyone sees that the transaction is occurring. Sometimes this
doesn't matter: most transactions are irrelevant for you and having to download them just wastes resources. But
occasionally you do wish to become aware that the ledger state has been changed by someone else. A simple example
is an option contract in which you wish to expire the option unless the counterparty has already exercised it. Them
exercising the option must not require the seller to sign off on it, as it may be advantageous for the seller to refuse
if it would cause them to lose money. Whilst the seller would discover if the buyer had exercised the option when they
attempted to expire it, due to the notary informing them that their expiry transaction was a double spend, it is
preferable to find out immediately.

The obvious way to implement this is to give notaries the responsibility for ensuring all interested parties find out
about a transaction. However, this would require the notaries to know who the involved parties actually are, which
would create an undesirable privacy leak. It would also place extra network load on the notaries who would frequently
be sending transaction data to parties that may already have it, or may simply not care. In many cases there may be
no requirement for the notary to act as a trusted third party for data distribution purposes, as game-theoretic
assumptions or legal assurances are sufficiently strong that peers can be trusted to deliver transaction data as part
of their regular flows.

To solve this, app developers can choose whether to request transaction distribution by the notary or not. This works
by simply piggybacking on the standard identity lookup flows (see~\cref{sec:identity-lookups}). If a node wishes to be
informed by the notary when a state is consumed, it can send the certificates linking the random keys in the state
to the notary cluster, which then stores it in the local databases as per usual. Once the notary cluster has committed
the transaction, key identities are looked up and any which resolve successfully are sent copies of the transaction. In
normal operation the notary is not provided with the certificates linking the random keys to the long term identity keys
and thus does not know who is involved with the operation (assuming source IP address obfuscation is in use, see~\cref{sec:privacy}).

\section{The vault}\label{sec:vault}

In any block chain based system most nodes have a wallet, or as we call it, a vault.

The vault contains data extracted from the ledger that is considered \emph{relevant} to the node's owner, stored in a form
that can be easily queried and worked with. It also contains private key material that is needed to sign transactions
consuming states in the vault. Like with a cryptocurrency wallet, the Corda vault understands how to create transactions
that send value to someone else by combining asset states and possibly adding a change output that makes the values
balance. This process is usually referred to as `coin selection'. Coin selection can be a complex process. In Corda
there are no per transaction network fees, which is a significant source of complexity in other systems. However
transactions must respect the fungibility rules in order to ensure that the issuer and reference data is preserved
as the assets pass from hand to hand.

Advanced vault implementations may also perform splitting and merging of states in the background. The purpose of this
is to increase the amount of transaction creation parallelism supported. Because signing a transaction may involve
human intervention (see~\cref{sec:secure-signing-devices}) and thus may take a significant amount of time, it can
become important to be able to create multiple transactions in parallel. The vault must manage state `soft locks' to
prevent multiple transactions trying to use the same output simultaneously. Violation of a soft lock would result in
a double spend being created and rejected by the notary. If a vault were to contain the entire cash balance
of a user in just one state, there could only be a single transaction being constructed at once and this could
impose unacceptable operational overheads on an organisation. By automatically creating send-to-self transactions that
split the big state into multiple smaller states, the number of transactions that can be created in parallel is
increased. Alternatively many tiny states may need to be consolidated into a smaller number of more valuable states
in order to avoid hitting transaction size limits. Finally, in some cases the vault may send asset states back
to the issuer for re-issuance, thus pruning long transaction chains and improving privacy.

The vault is also responsible for managing scheduled events requested by node-relevant states when the implementing app
has been installed (see~\cref{sec:event-scheduling}).

\subsection{Direct SQL access}

A distributed ledger is ultimately just a shared database, albeit one with some unique features. The following features
are therefore highly desirable for improving the productivity of app developers:

\begin{itemize}
\item Ability to store private data linked to the semi-public data in the ledger.
\item Ability to query the ledger data using widely understood tools like SQL.
\item Ability to perform joins between entirely app-private data (like customer notes) and ledger data.
\item Ability to define relational constraints and triggers on the underlying tables.
\item Ability to do queries at particular points in time e.g. midnight last night.
\item Re-use of industry standard and highly optimised database engines.
\item Independence from any particular database engine, without walling off too many useful features.
\end{itemize}

Corda states are defined using a subset of the JVM bytecode language which includes annotations. The vault recognises
annotations from the \emph{Java Persistence Architecture} (JPA) specification defined in JSR 338\cite{JPA}.
These annotations define how a class maps to a relational table schema including which member is the primary key, what
SQL types to map the fields to and so on. When a transaction is submitted to the vault by a flow, the vault finds
states it considers relevant (i.e. which contains a key owned by the node) and the relevant CorDapp has been installed
into the node as a plugin, the states are fed through an object relational mapper which generates SQL \texttt{UPDATE}
and \texttt{INSERT} statements. Note that data is not deleted when states are consumed, however a join can be performed
with a dedicated metadata table to eliminate consumed states from the dataset. This allows data to be queried at a point
in time, with rows being evicted to historical tables using external tools.

Nodes come with an embedded database engine out of the box, but may also be configured to point to a separate RDBMS.
The node stores not only state data but also all node working data in the database, including flow checkpoints. Thus
the state of a node and all communications it is engaged in can be backed up by simply backing up the database itself.
The JPA annotations are independent of any particular database engine or SQL dialect and thus states cannot use any
proprietary column types or other features, however, because the ORM is only used on the write paths users are free
to connect to the backing database directly and issue SQL queries that utilise any features of their chosen database
engine that they like. They can also create their own tables and create merged views of the underlying data for end
user applications, as long as they don't impose any constraints that would prevent the node from syncing the database
with the actual contents of the ledger.

% TODO: Artemis stores message queues separately right now, although it does have a JDBC backend we don't use it.

States are arbitrary object graphs. Whilst nothing stops a state from containing multiple classes intended for different
tables, it is typical that the relational representation will not be a direct translation of the object-graph
representation. States are queried by the vault for the ORM mapped class to use, which will often skip ledger-specific
data that's irrelevant to the user like opaque public keys and may expand single fields like an \texttt{Amount<Issued<Currency>>}
type into multiple database columns.

It's worth noting here that although the vault only responds to JPA annotations it is often useful for states to be
annotated in other ways, for instance to customise its mapping to XML/JSON, or to impose validation constraints~\cite{BeanValidation}. These annotations won't affect the behaviour of the node directly but may be useful when working
with states in surrounding software.

\subsection{Key randomisation}\label{sec:key-randomisation}

A standard privacy technique in block chain systems is the use of randomised unlinkable public keys to stand in for
actual verified identities. Ownership of these pseudonyms may be revealed to a counterparty using a simple interactive
protocol in which Alice selects a random nonce (`number used once') and sends it to Bob, who then signs the nonce with
the private key corresponding to the public key he is proving ownership of.

Generating fresh keys for each new deal or asset transfer rapidly results in many private keys being created. These
keys must all be backed up and kept safe, which poses a significant management problem when done at scale. The canonical
way to resolve this problem is through the use of deterministic key derivation, as pioneered by the Bitcoin community in
BIP 32 `Hierarchical Deterministic Wallets'\cite{BIP32}. Deterministic key derivation allows all private key
material needed to be derived from a single, small pool of entropy (e.g. a carefully protected and backed up 128 bits of
random data). More importantly, when the full BIP 32 technique is used in combination with an elliptic curve that supports
it, public keys may also be deterministically derived \emph{without} access to the underlying private key material. This
allows devices to provide fresh public keys to counterparties without being able to sign with those keys, enabling
better security along with operational efficiencies.

Corda does not place any constraints on the mathematical properties of the digital signature algorithms parties use.
However, implementations are recommended to use hierarchical deterministic key derivation when possible.

\section{Domain specific languages}

\subsection{Clauses}
When writing a smart contract, many desired features and patterns crop up repeatedly. For example it is expected
that all production quality asset contracts would want the following features:

\begin{itemize}
\item Issuance and exit transactions.
\item Movement transactions (reassignment of ownership).
\item Fungibility management (see~\cref{sec:tokens}).
\item Support for upgrading to new versions of the contract.
\end{itemize}

Many of these seemingly simple features have obscure edge cases. One example is a need to prevent the creation of
asset states that contain zero or negative quantities of the asset. Another is to ensure that states are summed
for fungibility purposes without accidentally assuming that the transaction only moves one type of asset at once.
Rather than expect contract developers to reimplement these pieces of low level logic the Corda standard library
provides \emph{clauses}, a small class library that implement reusable pieces of contract logic. A contract writer
may create their own clauses and then pass the set of contract clauses together to a library function that
interprets them.

\subsection{Combinator libraries}

Domain specific languages for the expression of financial contracts are a popular area of research. A seminal work
is `Composing contracts' by Peyton-Jones, Seward and Eber [PJSE2000\cite{PeytonJones:2000:CCA:357766.351267}] in which
financial contracts are modelled with a small library of Haskell combinators. These models can then be used for
valuation of the underlying deals. Block chain systems use the term `contract' in a slightly different sense to
how PJSE do but the underlying concepts can be adapted to our context as well. The platform provides an
experimental \emph{universal contract} that builds on the language extension features of the Kotlin programming
language. To avoid linguistic confusion it refers to the combined code/data bundle as an `arrangement' rather
than a contract. A European FX call option expressed in this language looks like this:

\newpage

\begin{kotlincode}
    val european_fx_option = arrange {
        actions {
            acmeCorp may {
                "exercise" anytime {
                    actions {
                        (acmeCorp or highStreetBank) may {
                            "execute".givenThat(after("2017-09-01")) {
                                highStreetBank.owes(acmeCorp, 1.M, EUR)
                                acmeCorp.owes(highStreetBank, 1200.K, USD)
                            }
                        }
                    }
                }
            }
            highStreetBank may {
                "expire".givenThat(after("2017-09-01")) {
                    zero
                }
            }
        }
    }
\end{kotlincode}

The programmer may define arbitrary `actions' along with constraints on when the actions may be invoked. The
\texttt{zero} token indicates the termination of the deal.

As can be seen, this DSL combines both \emph{what} is allowed and deal-specific data like \emph{when} and \emph{how much}
is allowed, therefore blurring the distinction the core model has between code and data. It builds on prior work
to enable not only valuation/cash flow calculations, but also direct enforcement of the contract's logic at the
database level as well.

\subsection{Formally verifiable languages}

Corda contracts can be upgraded. However, given the coordination problems inherent in convincing many participants
in a large network to accept a new version of a contract, a frequently cited desire is for formally verifiable
languages to be used to try and guarantee the correctness of the implementations.

We do not attempt to tackle this problem ourselves. However, because Corda focuses on deterministic execution of
any JVM bytecode, formally verifiable languages that target this instruction set are usable for the expression
of smart contracts. A good example of this is the Whiley language by Dr David Pearce\cite{Pearce2015191}, which
checks program-integrated proofs at compile time. By building on industry-standard platforms, we gain access to
cutting edge research from the computer science community outside of the distributed systems world.

\subsection{Projectional editing}

Custom languages and type systems for the expression of contract logic can be naturally combined with \emph{projectional
editing}, in which source code is not edited textually but rather by a structure aware
editor\cite{DBLP:conf/models/VoelterL14}. Such languages can consist not only of traditional grammar-driven text
oriented structures but also diagrams, tables and recursive compositions of them together. Given the frequent occurrence
of data tables and English-oriented nature of many financial contracts, a dedicated environment for the construction of
smart contract logic may be appreciated by the users.

\section{Secure signing devices}\label{sec:secure-signing-devices}

\subsection{Background}

A common feature of digital financial systems and block chain-type systems in particular is the use of secure client-side
hardware to hold private keys and perform signing operations with them. Combined with a zero tolerance approach to
transaction rollbacks, this is one of the ways they reduce overheads: by attempting to ensure that transaction
authorisation is robust and secure, and thus that signatures are reliable.

Many banks have rolled out CAP (chip authentication program) readers to consumers which allow logins to online banking using a
challenge/response protocol to a smartcard. The user is expected to type in the right codes and copy the responses back
to the computer by hand. These devices are cheap, but tend to have small, unreliable, low resolution screens and can be
subject to confusion attacks if there is malware on the PC, e.g. if the malware convinces the user they are performing
a login challenge whereas in fact they are authorising a payment to a new account. The primary advantage is that the
signing key is held in a robust and cheap smart card, so the device can be replaced without replacing the key.

The state-of-the-art in this space are devices like the TREZOR\cite{TREZOR} by Satoshi Labs or the Ledger Blue. These
were developed by and for the Bitcoin community. They are more expensive than CAP readers and feature better
screens and USB connections to eliminate typing. Advanced devices like the Ledger Blue support NFC and
Bluetooth as well. These devices differ from CAP readers in another key respect: instead of signing arbitrary, small
challenge numbers, they actually understand the native transaction format of the network to which they're specialised and parse the
transaction to figure out the message to present to the user, who then confirms that they wish to perform the action
printed on the screen by simply pressing a button. The transaction is then signed internally before being passed back to
the PC via the USB/NFC/Bluetooth connection.

This setup means that rather than having a small device that authorises to a powerful server (which controls all your
assets), the device itself controls the assets. As there is no smartcard equivalent the private key can be exported off
the device by writing it down in the form of ``wallet words'': 12 random words derived from the contents of the key.
Because elliptic curve private keys are small (256 bits), this is not as tedious as it would be with the much larger RSA
keys the financial industry is typically using.

There are clear benefits to having signing keys be kept on personal, employee-controlled devices only, with the organisation's
node not having any ability to sign for transactions itself:

\begin{itemize}
\item If the node is hacked by a malicious intruder or bad insider they cannot steal assets, modify agreements,
or do anything else that requires human approval, because they don't have access to the signing keys. There is no single
point of failure from a key management perspective.
\item It's more clear who signed off on a particular action -- the signatures prove which devices were used to sign off
on an action. There can't be any back doors or administrator tools which can create transactions on behalf of someone else.
\item Devices that integrate fingerprint readers and other biometric authentication could further increase trust by
making it harder for employees to share/swap devices. A smartphone or tablet could be also used as a transaction authenticator.
\end{itemize}

\subsection{Confusion attacks}

The biggest problem facing anyone wanting to integrate smart signing devices into a distributed ledger system is how the
device processes transactions. For Bitcoin it's straightforward for devices to process transactions directly because
their format is very small and simple (in theory -- in practice a fixable quirk of the Bitcoin protocol actually
significantly complicates how these devices must work). Thus turning a Bitcoin transaction into a human meaningful
confirmation screen is quite easy:

\indent\texttt{Confirm payment of 1.23 BTC to 1AbCd0123456.......}

This confirmation message is susceptible to confusion attacks because the opaque payment address is unpredictable. A
sufficiently smart virus/attacker could have swapped out a legitimate address of a legitimate counterparty you are
expecting to pay with one of their own, thus you'd pay the right amount to the wrong place. The same problem can affect
financial authenticators that verify IBANs and other account numbers: the user's source of the IBAN may be an email or
website they are viewing through the compromised machine. The BIP 70\cite{BIP70} protocol was designed to address this
attack by allowing a certificate chain to be presented that linked a target key with a stable, human meaningful and
verified identity.

For a generic ledger we are faced with the additional problem that transactions may be of many different types,
including new types created after the device was manufactured. Thus creating a succinct confirmation message inside the
device would become an ever-changing problem requiring frequent firmware updates. As firmware upgrades are a potential
weak point in any secure hardware scheme, it would be ideal to minimise their number.

\subsection{Transaction summaries}

To solve this problem we add a top level summaries field to the transaction format (joining inputs, outputs, commands,
attachments etc). This new top level field is a list of strings. Smart contracts get a new responsibility. They are
expected to generate an English message describing what the transaction is doing, and then check that it is present in
the transaction. The platform ensures no unexpected messages are present. The field is a list of strings rather than
a single string because a transaction may do multiple things simultaneously in advanced use cases.

Because the calculation of the confirmation message has now been moved to the smart contract itself, and is a part of
the transaction, the transaction can be sent to the signing device: all it needs to do is extract the messages and
print them to the screen with YES/NO buttons available to decide whether to sign or not. Because the device's signature
covers the messages, and the messages are checked by the contract based on the machine readable data in the states, we
can know that the message was correct and legitimate.

The design above is simple but has the issue that large amounts of data are sent to the device which it doesn't need.
As it's common for signing devices to have constrained memory, it would be unfortunate if the complexity of a transaction
ended up being limited by the RAM available in the users' signing devices. To solve this we can use the tear-offs
mechanism (see~\cref{sec:tear-offs}) to present only the summaries and the Merkle branch connecting them to the root.
The device can then sign the entire transaction contents having seen only the textual summaries, knowing that the states
will trigger the contracts which will trigger the summary checks, thus the signature covers the machine-understandable
version of the transaction as well.

Note, we assume here that contracts are not themselves malicious. Whilst a malicious user could construct a contract that
generated misleading messages, for a user to see states in their vault and work with them requires the accompanying
CorDapp to be loaded into the node as a plugin and thus whitelisted. There is never a case where the user may be asked
to sign a transaction involving contracts they have not previously approved, even though the node may execute such
contracts as part of verifying transaction dependencies.

\subsection{Identity substitution}

Contract code only works with opaque representations of public keys. Because transactions in a chain of custody may need
to be anonymised, it isn't possible for a contract to access identity information from inside the sandbox. Therefore it
cannot generate a complete message that includes human meaningful identity names even if the node itself does have this
information.

To solve this the transaction is provided to the device along with the X.509 certificate chains
linking the pseudonymous public keys to the long term identity certificates, which for transactions involving the user
should always be available (as they by definition know who their trading counterparties are). The device can verify
those certificate chains to build up a mapping of index to human readable name. The messages placed inside a transaction may contain numeric indexes of the public keys required by the
commands using backslash syntax, and the device must perform the message substitution before rendering.
Care must be taken to ensure that the X.500 names issued to network participants do not contain text chosen to
deliberately confuse users, e.g. names that contain quote marks, partial instructions, special symbols and so on.
This can be enforced at the network permissioning level.

\subsection{Multi-lingual support}

The contract is expected to generate a human readable version of the transaction. This should be in English, by
convention. In theory, we could define the transaction format to support messages in different languages, and if
the contract supported that the right language could then be picked by the signing device. However, care must be taken
to ensure that the message the user sees in alternative languages is correctly translated and not subject to ambiguity
or confusion, as otherwise exploitable confusion attacks may arise.

\section{Client RPC and reactive collections}

Any realistic deployment of a distributed ledger faces the issue of integration with an existing ecosystem of
surrounding tools and processes. Ideally, programs that interact with the node will be loosely coupled,
authenticated, robust against transient node outages and restarts, and speed differences (e.g. production of
work being faster than completion of work) will be handled transparently.

To meet these needs, Corda nodes expose a simple RPC mechanism that has a couple of unusual features. The underlying
transport is message queues (AMQP) and methods can return object graphs that contain Rx observables\cite{Rx} which may
in turn emit more observables.

It is a common pattern for RPCs to return a snapshot of some data structure, along with an observable that emits
objects representing a delta on that data structure. The client library has functionality to reconstruct the
snapshot + diffs into a observable collections of the type that can be bound directly to a JavaFX user interface.
In this way, rendering data structures in the global ledger in a rich client app that stays fresh becomes a
straightforward operation that requires minimal work from the developer: simply wiring the pieces together in
a functional way is sufficient. Reactive transforms over these observable collections such as mappings,
filterings, sortings and so on make it easy to build user interfaces in a functional programming style.

Because RPC transport takes place via the node's message queue broker, the framework automatically recovers
from restarts of the node/node components, IP addresses changes on the client and similar interruptions to
communication. Likewise, programs that need to live for a long time and survive restarts, upgrades and moves
can request that observations be sent to a persistent queue. Backpressure and queue management is supplied by
the broker. Additional capacity for processing RPCs can be added by attaching more RPC processors to the broker
which load balances between them automatically.

It can be asked why Corda does not use the typical REST+JSON approach to communicating with the node. The reasons
are:

\begin{itemize}
\item A preference for binary protocols over textual protocols, as text based protocols tend to be more
susceptible to escaping and other buffer management problems that can lead to security issues.
\item Message queue brokers provide significant amounts of infrastructure for building reliable apps
which plain HTTP does not such as backpressure management, load balancing, queue browsing, management of speed
differences and so on.
\item REST based protocols have multiple conventions for streaming of results back to the client, none of which
are ideal for the task.
\end{itemize}

% TODO: current RPC framework doesn't configure persistence or backpressure management.
% TODO: currently you can't bring online rpc processors independently of the rest of the node.

Being able to connect live data structures directly to UI toolkits also contributes to the avoidance
of XSS exploits, XSRF exploits and similar security problems based on losing track of buffer boundaries.

\section{Data distribution groups}

By default, distribution of transaction data is defined by app-provided flows (see~\cref{sec:flows}). Flows specify
when and to which peers transactions should be sent. Typically these destinations will be calculated based on the content
of the states and the available identity lookup certificates, as the intended use case of financial data usually
contains the identities of the relevant parties within it. Sometimes though, the set of parties that should receive
data isn't known ahead of time and may change after a transaction has been created. For these cases partial data
visibility is not a good fit and an alternative mechanism is needed.

A data distribution group (DDG) is created by generating a keypair and a self-signed certificate for it. Groups are
identified internally by their public key and may be given string names in the certificate, but nothing in the
software assumes the name is unique: it's intended only for human consumption and it may conflict with other independent
groups. In case of conflict user interfaces disambiguate by appending a few characters of the base58 encoded public key
to the name like so:  "My popular group name (a4T)". As groups are not globally visible anyway, it is unlikely that
conflicts will be common or require many code letters to deconflict, and some groups may not even be intended for
human consumption at all.

Once a group is created other nodes can be invited to join it by using an invitation flow. Membership can be either
read only or read/write. To add a node as read-only, the certificate i.e. pubkey alone is sent. To add a node as
read/write the certificate and private key are sent. A future elaboration on the design may support giving each member a
separate private key which would allow tracing who added transactions to a group, but this is left for future work.
In either case the node records in its local database which other nodes it has invited to the group once they accept
the invitation.

When the invite is received the target node runs the other side of the flow as normal, which may either automatically
accept membership if it's configured to trust the inviting node, or send a message to a message queue for processing by an
external system, or kick it up to a human administrator for approval. Invites to groups the node is already a
member of are rejected. The accepting node also records which node invited it. So, there ends up being a two-way
recorded relationship between inviter and invitee stored in their vaults. Finally the inviter side of the
invitation flow pushes a list of all the transaction IDs that exist in the group and the invitee side resolves all of
them. The end result is that all the transactions that are in the group are sent to the new node (along with all
dependencies).

Note that this initial download is potentially infinite if transactions are added to the group as fast or faster than the
new node is downloading and checking them. Thus whilst it may be tempting to try and expose a notion of `doneness' to
the act of joining a group, it's better to see the act of joining as happening at a specific point in time and the
resultant flood of transaction data as an ongoing stream, rather than being like a traditional file download.

When a transaction is sent to the vault, it always undergoes a relevancy test, regardless of whether it is in a group
or not (see~\cref{sec:vault}). This test is extended to check also for the
signatures of any groups the node is a member of. If there's a match then the transaction's states are all considered
relevant. In addition, the vault looks up which nodes it invited to this group, and also which nodes invited it, removes
any nodes that have recently sent us this transaction and then kicks off a \texttt{PropagateTransactionToGroup} flow
with each of them.  The other side of this flow checks if the transaction is already known, if not requests it, checks
that it is indeed signed by the group in question, resolves it and then assuming success, sends it to the vault. In this
way a transaction added by any member of the group propagates up and down the membership tree until all the members have
seen it. Propagation is idempotent -- if the vault has already seen a transaction before then it isn't processed again.

The structure we have so far has some advantages and one big disadvantage. The advantages are:

\begin{itemize}
\item [Simplicity] The core data model is unchanged. Access control is handled using existing tools like signatures, certificates and flows.
\item [Privacy] It is possible to join a group without the other members being aware that you have done so. It is possible to create groups without non-members knowing the group exists.
\item [Scalability] Groups are not registered in any central directory. A group that exists between four parties imposes costs only on those four.
\item [Performance] Groups can be created as fast as you can generate keypairs and invite other nodes to join you.
\item [Responsibility] For every member of the group there is always a node that has a responsibility for sending you
new data under the protocol (the inviting node). Unlike with Kademlia style distributed hash tables, or Bitcoin style
global broadcast, you can never find yourself in a position where you didn't receive data yet nobody has violated the
protocol. There are no points at which you pick a random selection of nodes and politely ask them to do something for
you, hoping that they'll choose to stick around.
\end{itemize}

The big disadvantage is that it's brittle. If you have a membership tree and a node goes offline for a while,
then propagation of data will split and back up in the outbound queues of the parents and children of the offline
node until it comes back.

To strengthen groups we can add a new feature, membership broadcasts. Members of the group that have write access may
choose to sign a membership announcement and propagate it through the tree. These announcements are recorded in the
local database of each node in the group. Nodes may include these announced members when sending newly added
transactions. This converts the membership tree to a graph that may contain cycles, but infinite propagation loops are
not possible because nodes ignore announcements of new transactions/attachments they've already received. Whether a group
prefers privacy or availability may be hinted in the certificate that defines it: if availability is preferred, this is
a signal that members should always announce themselves (which would lead to a mesh).

The network map for a network defines the event horizon, the span of time that is allowed to elapse before an offline
node is considered to be permanently gone. Once a peer has been offline for longer than the event horizon any nodes that
invited it remove it from their local tables. If a node was invited to a group by a gone peer and there are no other
nodes that announced their membership it can use, the node should post a message to a queue and/or notify the
administrator, as it's now effectively been evicted from the group.

The resulting arrangement may appear similar to a gossip network. However the underlying membership tree structure
remains. Thus when all nodes are online (or online enough) messages are guaranteed to propagate to everyone in the
network. You can't get situations where a part of the group has become split from the rest without anyone being aware of
that fact; an unlikely but possible occurrence in a gossip network. It also isn't like a distributed hash table where
data isn't fully replicated, so we avoid situations where data has been added to the group but stops being available due
to node outages. It is always possible to reason about the behaviour of the network and always possible to assign
responsibility if something goes wrong.

Note that it is not possible to remove members after they have been added to a group. We could provide a remove
announcement but it'd be advisory only: nothing stops nodes from ignoring it. It is also not possible to enumerate
members of a group because there is no requirement to do a membership broadcast when you join and no way to enforce such
a requirement.

% TODO: Nothing related to data distribution groups is implemented.

\section{Deterministic JVM}\label{sec:djvm}

It is important that all nodes that process a transaction always agree on whether it is valid or not. Because
transaction types are defined using JVM bytecode, this means the execution of that bytecode must be fully
deterministic. Out of the box a standard JVM is not fully deterministic, thus we must make some modifications
in order to satisfy our requirements. Non-determinism could come from the following sources:

\begin{itemize}
\item Sources of external input e.g. the file system, network, system properties, clocks.
\item Random number generators.
\item Different decisions about when to terminate long running programs.
\item \texttt{Object.hashCode()}, which is typically implemented either by returning a pointer address or by
assigning the object a random number. This can surface as different iteration orders over hash maps and hash sets.
\item Differences in hardware floating point arithmetic.
\item Multi-threading.
\item Differences in API implementations between nodes.
\item Garbage collector callbacks.
\end{itemize}

To ensure that the contract verify function is fully pure even in the face of infinite loops we construct a new
type of JVM sandbox. It utilises a bytecode static analysis and rewriting pass, along with a small JVM patch that
allows the sandbox to control the behaviour of hashcode generation. Contract code is rewritten the first time
it needs to be executed and then stored for future use.

The bytecode analysis and rewrite performs the following tasks:

\begin{itemize}
\item Inserts calls to an accounting object before expensive bytecodes. The goal of this rewrite is to deterministically
terminate code that has run for an unacceptably long amount of time or used an unacceptable amount of memory. Expensive
bytecodes include method invocation, allocation, backwards jumps and throwing exceptions.
\item Prevents exception handlers from catching \texttt{Throwable}, \texttt{Error} or \texttt{ThreadDeath}.
\item Adjusts constant pool references to relink the code against a `shadow' JDK, which duplicates a subset of the regular
JDK but inside a dedicated sandbox package. The shadow JDK is missing functionality that contract code shouldn't have access
to, such as file IO or external entropy.
\item Sets the \texttt{strictfp} flag on all methods, which requires the JVM to do floating point arithmetic in a hardware
independent fashion. Whilst we anticipate that floating point arithmetic is unlikely to feature in most smart contracts
(big integer and big decimal libraries are available), it is available for those who want to use it.
\item Forbids \texttt{invokedynamic} bytecode except in special cases, as the libraries that support this functionality have
historically had security problems and it is primarily needed only by scripting languages. Support for the specific
lambda and string concatenation metafactories used by Java code itself are allowed.
% TODO: The sandbox doesn't allow lambda/string concat(j9) metafactories at the moment.
\item Forbids native methods.
\item Forbids finalizers.
\end{itemize}

The cost instrumentation strategy used is a simple one: just counting bytecodes that are known to be expensive to execute.
Method size is limited and jumps count towards the budget, so such a strategy is guaranteed to eventually terminate. However
it is still possible to construct bytecode sequences by hand that take excessive amounts of time to execute. The cost
instrumentation is designed to ensure that infinite loops are terminated and that if the cost of verifying a transaction
becomes unexpectedly large (e.g. contains algorithms with complexity exponential in transaction size) that all nodes agree
precisely on when to quit. It is \emph{not} intended as a protection against denial of service attacks. If a node is sending
you transactions that appear designed to simply waste your CPU time then simply blocking that node is sufficient to solve
the problem, given the lack of global broadcast.

Opcode budgets are separate per opcode type, so there is no unified cost model. Additionally the instrumentation is high
overhead. A more sophisticated design would be to statically calculate bytecode costs as much as possible ahead of time,
by instrumenting only the entry point of `accounting blocks', i.e. runs of basic blocks that end with either a method return
or a backwards jump. Because only an abstract cost matters (this is not a profiler tool) and because the limits are expected
to bet set relatively high, there is no need to instrument every basic block. Using the max of both sides of a branch is
sufficient when neither branch target contains a backwards jump. This sort of design will be investigated if the per category
opcode-at-a-time accounting turns out to be insufficient.

A further complexity comes from the need to constrain memory usage. The sandbox imposes a quota on bytes \emph{allocated}
rather than bytes \emph{retained} in order to simplify the implementation. This strategy is unnecessarily harsh on smart
contracts that churn large quantities of garbage yet have relatively small peak heap sizes and, again, it may be that
in practice a more sophisticated strategy that integrates with the garbage collector is required in order to set
quotas to a usefully generic level.

Control over \texttt{Object.hashCode()} takes the form of new JNI calls that allow the JVM's thread local random number
generator to be reseeded before execution begins. The seed is derived from the hash of the transaction being verified.

Finally, it is important to note that not just smart contract code is instrumented, but all code that it can transitively
reach. In particular this means that the `shadow JDK' is also instrumented and stored on disk ahead of time.

\section{Scalability}

Scalability of block chains and block chain inspired systems has been a constant topic of discussion since Nakamoto
first proposed the technology in 2008. We make a variety of choices and tradeoffs that affect and
ensure scalability. As most of the initial intended use cases do not involve very high levels of traffic, the
reference implementation is not heavily optimised. However, the architecture allows for much greater levels of
scalability to be achieved when desired.

\paragraph{Partial visibility.}Nodes only encounter transactions if they are involved in some way, or if the
transactions are dependencies of transactions that involve them in some way. This loosely connected
design means that it is entirely possible for most nodes to never see most of the transaction graph, and thus
they do not need to process it. This makes direct scaling comparisons with other distributed and
decentralised database systems difficult, as they invariably measure performance in transctions/second.
For Corda, as writes are lazily replicated on demand, it is difficult to quote a transactions/second figure for
the whole network.

\paragraph{Distributed node.}At the center of a Corda node is a message queue broker. Nodes are logically structured
as a series of microservices and have the potential in future to be run on separate machines. For example, the
embedded relational database can be swapped out for an external database that runs on dedicated hardware. Whilst
a single flow cannot be parallelised, a node under heavy load would typically be running many flows in parallel.
As flows access the network via the broker and local state via an ordinary database connection, more flow processing
capacity could be added by just bringing online additional flow workers. This is likewise the case for RPC processing.

\paragraph{Signatures outside the transactions.}Corda transaction identifiers are the root of a Merkle tree
calculated over its contents excluding signatures. This has the downside that a signed and partially signed
transaction cannot be distinguished by their canonical identifier, but means that signatures can easily be
verified in parallel. Corda smart contracts are deliberately isolated from the underlying cryptography and are
not able to request signature checks themselves: they are run \emph{after} signature verification has
taken place and don't execute at all if required signatures are missing. This ensures that signatures for a single
transaction can be checked concurrently even though the smart contract code for that transaction is not parallelisable.
(note that unlike some other systems, transactions involving the same contracts \emph{can} be checked in parallel.)

\paragraph{Multiple notaries.}It is possible to increase scalability in some cases by bringing online additional
notary clusters. Note that this only adds capacity if the transaction graph has underlying exploitable structure
(e.g. geographical biases), as a purely random transaction graph would end up constantly crossing notaries and
the additional transactions to move states from one notary to another would negate the benefit. In real
trading however the transaction graph is not random at all, and thus this approach may be helpful.

\paragraph{Asset reissuance.}In the case where the issuer of an asset is both trustworthy and online, they may
exit and re-issue an asset state back onto the ledger with a new reference field. This effectively truncates the
dependency graph of that asset which both improves privacy and scalability, at the cost of losing atomicity (it
is possible for the issuer to exit the asset but not re-issue it, either through incompetence or malice).

\paragraph{Non-validating notaries.}The overhead of checking a transaction for validity before it is notarised is
likely to be the main overhead for non-BFT notaries. In the case where raw throughput is more important than
ledger integrity it is possible to use a non-validating notary. See~\cref{sec:non-validating-notaries}.

The primary bottleneck in a Corda network is expected to be the notary clusters, especially for byzantine fault
tolerant (BFT) clusters made up of mutually distrusting nodes. BFT clusters are likely to be slower partly because the
underlying protocols are typically chatty and latency sensitive, and partly because the primary situation when
using a BFT protocol is beneficial is when there is no shared legal system which can be used to resolve fraud or
other disputes, i.e. when cluster participants are spread around the world and thus the speed of light becomes
a major limiting factor.

The primary bottleneck in a Corda node is expected to be flow checkpointing, as this process involves walking the
stack and heap then writing out the snapshotted state to stable storage. Both of these operations are computationally
intensive. This may seem unexpected, as other platforms typically bottleneck on signature
checking operations. It is worth noting though that the main reason other platforms do not bottleneck
on checkpointing operations is that they typically don't provide any kind of app-level robustness services
at all, and so the cost of checkpointing state (which must be paid eventually!) is accounted to the application
developer rather than the platform. When a flow developer knows that a network communication is idempotent and
thus can be replayed, they can opt out of the checkpointing process to gain throughput at the cost of additional
wasted work if the flow needs to be evicted to disk. Note that checkpoints and transaction data can be stored in
any NoSQL database (such as Cassandra), at the cost of a more complex backup strategy.

% TODO: Opting out of checkpointing isn't available yet.
% TODO: Ref impl doesn't support using a NoSQL store for flow checkpoints.

Due to partial visibility nodes check transaction graphs `just in time' rather than as a steady stream of
announcements by other participants. This complicates the question of how to measure the scalability of a Corda
node. Other block chain systems quote performance as a constant rate of transactions per unit time.
However, our `unit time' is not evenly distributed: being able to check 1000 transactions/sec is not
necessarily good enough if on presentation of a valuable asset you need to check a transation graph that consists
of many more transactions and the user is expecting the transaction to show up instantly. Future versions of
the platform may provide features that allow developers to smooth out the spikey nature of Corda transaction
checking by, for example, pre-pushing transactions to a node when the developer knows they will soon request
the data anyway.

\section{Privacy}\label{sec:privacy}

Privacy is not a standalone feature in the way that many other aspects described in this paper are, so this section
summarises features described elsewhere. Corda exploits multiple techniques to improve user privacy over other
distributed ledger systems:

\paragraph{Partial data visibility.}Transactions are not globally broadcast as in many other systems.
\paragraph{Transaction tear-offs.}Transactions are structured as Merkle trees, and may have individual subcomponents be
revealed to parties who already know the Merkle root hash. Additionally, they may sign the transaction without being
able to see all of it. See~\cref{sec:tear-offs}
\paragraph{Key randomisation.}The vault generates and uses random keys that are unlinkable to an identity without the
corresponding linkage certificate. See~\cref{sec:vault}.
\paragraph{Graph pruning.}Large transaction graphs that involve liquid assets can be `pruned' by requesting the asset
issuer to re-issue the asset onto the ledger with a new reference field. This operation is not atomic, but effectively
unlinks the new version of the asset from the old, meaning that nodes won't attempt to explore the original dependency
graph during verification.

Corda has been designed with the future integration of additional privacy technologies in mind. Of all potential
upgrades, three are particularly worth a mention.

\paragraph{Secure hardware.}Although we narrow the scope of data propagation to only nodes that need to see that
data, `need' can still be an unintuitive concept in a decentralised database where often data is required only
to perform security checks. We have successfully experimented with running contract verification inside a
secure enclave protected JVM using Intel SGX\texttrademark~, an implementation of the `trusted computing'
concept\cite{mitchell2005trusted}. Secure hardware platforms allow computation to be performed
in an undebuggable tamper-proof execution environment, for the software running inside that environment to derive
encryption keys accessible only to that instance, and for the software to \emph{remotely attest} to a third party
over the internet that it is indeed running in the secure state. By having nodes remotely attest to each other
that they are running smart contract verification logic inside an enclave it becomes possible for the dependencies
of a transaction to be transmitted to a peer encrypted under an enclave key, thus allowing them to
verify the dependencies using software they have audited themselves, but without being able to see the data on
which it operates.

Secure hardware opens up the potential for a one-shot privacy model that would dramatically simplify the task
of writing smart contracts. However, it does still require the sensitive data to be sent to the peer
who may then attempt to attack the hardware or exploit side channels to extract business intelligence from
inside the encrypted container.

\paragraph{Mix networks.}Some nodes may be in the position of learning about transactions that aren't directly related
to trades they are doing, for example notaries or regulator nodes. Even when key randomisation is used these nodes can
still learn valuable identity information by simply examining the source IP addresses or the authentication certificates
of the nodes sending the data for notarisation. The traditional cryptographic solution to this problem is a
\emph{mix network}\cite{Chaum:1981:UEM:358549.358563}. The most famous mix network is Tor, but a more appropriate design
for Corda would be that of an anonymous remailer. In a mix network a message is repeatedly encrypted in an onion-like
fashion using keys owned by a small set of randomly selected nodes. Each layer in the onion contains the address of the
next `hop'. Once the message is delivered to the first hop, it decrypts it to reveal the next encrypted layer and
forwards it onwards. The return path operates in a similar fashion. Adding a mix network to the Corda protocol
would allow users to opt-in to a privacy upgrade, at the cost of higher latencies and more exposure to failed network
nodes.

\paragraph{Zero knowledge proofs.}The holy grail of privacy in decentralised database systems is the use of zero
knowledge proofs to convince a peer that a transaction is valid, without revealing the contents of the transaction to
them. Although these techniques are not yet practical for execution of general purpose smart contracts, enormous
progress has been made in recent years and we have designed our data model on the assumption that we will one day wish
to migrate to the use of \emph{zero knowledge succinct non-interactive arguments of knowledge}\cite{184425}
(`zkSNARKs'). These algorithms allow for the calculation of a fixed-size mathematical proof that a program was correctly
executed with a mix of public and private inputs. Programs can be expressed either directly as a system of low-degree
multivariate polynomials encoding an algebraic constraint system, or by execution on a simple simulated CPU (`vnTinyRAM') which is itself
implemented as a large pre-computed set of constraints. Because the program is shared the combination of an
agreed upon function (i.e. a smart contract) along with private input data is sufficient to verify correctness,
as long as the prover's program may recursively verify other proofs, i.e. the proofs of the input transactions.
The BCTV zkSNARK algorithms rely on recursive proof composition for the execution of vnTinyRAM opcodes, so this is not a
problem. The most obvious integration with Corda would require tightly written assembly language versions of common
smart contracts (e.g. cash) to be written by hand and aligned with the JVM versions. Less obvious but more powerful
integrations would involve the addition of a vnTinyRAM backend to an ahead of time JVM bytecode compiler, such as
Graal\cite{Graal}, or a direct translation of Graal's graph based intermediate representation into systems of constraints.
Direct translation of an SSA-form compiler IR to constraints would be best integrated with recent research
into `scalable probabilistically checkable proofs'\cite{cryptoeprint:2016:646}, and is an open research problem.

\section{Conclusion}

We have presented Corda, a decentralised database designed for the financial sector. It allows for a unified data set to be
distributed amongst many mutually distrusting nodes, with smart contracts running on the JVM
providing access control and schema definitions. A novel continuation-based persistence framework assists
developers with coordinating the flow of data across the network. An identity management system ensures that
parties always know who they are trading with. Notaries ensure algorithmic agility with respect to distributed
consensus systems, and the system operates without mining or a block chain.

A standard type system is provided for the modelling of financial logic. The design considers security throughout: it
supports the integration of secure signing devices for transaction authorisation, secure enclaves for transaction
processing, composite keys for expressing complex authorisation policies, and is based on binary protocols with
length-prefixed buffers throughout for the systematic avoidance of common buffer management exploits. Users may analyse
ledger data relevant to them by issuing ordinary SQL queries against mature database engines, and may craft complex
multi-party transactions with ease in programming languages that are already familiar to them.

Finally, the platform defines standard ways to integrate the global ledger with financial infrastructure like high
performance markets and netting services.

\section{Acknowledgements}

The author would like to thank Richard Gendal Brown, James Carlyle, Shams Asari, Rick Parker, Andras Slemmer, Ross
Nicoll, Andrius Dagys, Matthew Nesbit, Jose Coll, Katarzyna Streich, Clinton Alexander, Patrick Kuo, Richard Green, Ian
Grigg, Mark Oldfield and Roger Willis for their insights and contributions to this design. We would also like to thank
Sofus Mortesen for his work on the universal contract DSL, and the numerous architects and subject matter experts
at financial institutions around the world who contributed their knowledge, requirements and ideas. Thanks also to
the authors of the many frameworks, protocols and components we have built upon.

Finally, we would like to thank Satoshi Nakamoto. Without him none of it would have been possible.

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