Protocol state machines¶

Introduction¶

Shared distributed ledgers are interesting because they allow many different, mutually distrusting parties to share a single source of truth about the ownership of assets. Digitally signed transactions are used to update that shared ledger, and transactions may alter many states simultaneously and atomically.

Blockchain systems such as Bitcoin support the idea of building up a finished, signed transaction by passing around partially signed invalid transactions outside of the main network, and by doing this you can implement delivery versus payment such that there is no chance of settlement failure, because the movement of cash and the traded asset are performed atomically by the same transaction. To perform such a trade involves a multi-step protocol in which messages are passed back and forth privately between parties, checked, signed and so on.

Despite how useful these protocols are, platforms such as Bitcoin and Ethereum do not assist the developer with the rather tricky task of actually building them. That is unfortunate. There are many awkward problems in their implementation that a good platform would take care of for you, problems like:

• Avoiding “callback hell” in which code that should ideally be sequential is turned into an unreadable mess due to the desire to avoid using up a thread for every protocol instantiation.
• Surviving node shutdowns/restarts that may occur in the middle of the protocol without complicating things. This implies that the state of the protocol must be persisted to disk.
• Error handling.
• Message routing.
• Serialisation.
• Catching type errors, in which the developer gets temporarily confused and expects to receive/send one type of message when actually they need to receive/send another.
• Unit testing of the finished protocol.

Actor frameworks can solve some of the above but they are often tightly bound to a particular messaging layer, and we would like to keep a clean separation. Additionally, they are typically not type safe, and don’t make persistence or writing sequential code much easier.

To put these problems in perspective, the payment channel protocol in the bitcoinj library, which allows bitcoins to be temporarily moved off-chain and traded at high speed between two parties in private, consists of about 7000 lines of Java and took over a month of full time work to develop. Most of that code is concerned with the details of persistence, message passing, lifecycle management, error handling and callback management. Because the business logic is quite spread out the code can be difficult to read and debug.

As small contract-specific trading protocols are a common occurence in finance, we provide a framework for the construction of them that automatically handles many of the concerns outlined above.

Theory¶

A continuation is a suspended stack frame stored in a regular object that can be passed around, serialised, unserialised and resumed from where it was suspended. This concept is sometimes referred to as “fibers”. This may sound abstract but don’t worry, the examples below will make it clearer. The JVM does not natively support continuations, so we implement them using a library called Quasar which works through behind-the-scenes bytecode rewriting. You don’t have to know how this works to benefit from it, however.

We use continuations for the following reasons:

• It allows us to write code that is free of callbacks, that looks like ordinary sequential code.
• A suspended continuation takes far less memory than a suspended thread. It can be as low as a few hundred bytes. In contrast a suspended Java thread stack can easily be 1mb in size.
• It frees the developer from thinking (much) about persistence and serialisation.

A state machine is a piece of code that moves through various states. These are not the same as states in the data model (that represent facts about the world on the ledger), but rather indicate different stages in the progression of a multi-stage protocol. Typically writing a state machine would require the use of a big switch statement and some explicit variables to keep track of where you’re up to. The use of continuations avoids this hassle.

A two party trading protocol¶

We would like to implement the “hello world” of shared transaction building protocols: a seller wishes to sell some asset (e.g. some commercial paper) in return for cash. The buyer wishes to purchase the asset using his cash. They want the trade to be atomic so neither side is exposed to the risk of settlement failure. We assume that the buyer and seller have found each other and arranged the details on some exchange, or over the counter. The details of how the trade is arranged isn’t covered in this article.

Our protocol has two parties (B and S for buyer and seller) and will proceed as follows:

1. S sends a StateAndRef pointing to the state they want to sell to B, along with info about the price they require B to pay.
2. B sends to S a SignedTransaction that includes the state as input, B’s cash as input, the state with the new owner key as output, and any change cash as output. It contains a single signature from B but isn’t valid because it lacks a signature from S authorising movement of the asset.
3. S signs it and hands the now finalised SignedTransaction back to B.

You can find the implementation of this protocol in the file contracts/protocols/TwoPartyTradeProtocol.kt.

Assuming no malicious termination, they both end the protocol being in posession of a valid, signed transaction that represents an atomic asset swap.

Note that it’s the seller who initiates contact with the buyer, not vice-versa as you might imagine.

We start by defining a wrapper that namespaces the protocol code, two functions to start either the buy or sell side of the protocol, and two classes that will contain the protocol definition. We also pick what data will be used by each side.

object TwoPartyTradeProtocol {
    val TRADE_TOPIC = "platform.trade"

    fun runSeller(smm: StateMachineManager, timestampingAuthority: LegallyIdentifiableNode,
                  otherSide: SingleMessageRecipient, assetToSell: StateAndRef<OwnableState>, price: Amount,
                  myKeyPair: KeyPair, buyerSessionID: Long): ListenableFuture<SignedTransaction> {
        val seller = Seller(otherSide, timestampingAuthority, assetToSell, price, myKeyPair, buyerSessionID)
        smm.add("$TRADE_TOPIC.seller", seller)
        return seller.resultFuture
    }

    fun runBuyer(smm: StateMachineManager, timestampingAuthority: LegallyIdentifiableNode,
                 otherSide: SingleMessageRecipient, acceptablePrice: Amount, typeToBuy: Class<out OwnableState>,
                 sessionID: Long): ListenableFuture<SignedTransaction> {
        val buyer = Buyer(otherSide, timestampingAuthority.identity, acceptablePrice, typeToBuy, sessionID)
        smm.add("$TRADE_TOPIC.buyer", buyer)
        return buyer.resultFuture
    }

    // This object is serialised to the network and is the first protocol message the seller sends to the buyer.
    class SellerTradeInfo(
            val assetForSale: StateAndRef<OwnableState>,
            val price: Amount,
            val sellerOwnerKey: PublicKey,
            val sessionID: Long
    )

    class SignaturesFromSeller(val timestampAuthoritySig: DigitalSignature.WithKey, val sellerSig: DigitalSignature.WithKey)

    class Seller(val otherSide: SingleMessageRecipient,
                 val timestampingAuthority: LegallyIdentifiableNode,
                 val assetToSell: StateAndRef<OwnableState>,
                 val price: Amount,
                 val myKeyPair: KeyPair,
                 val buyerSessionID: Long) : ProtocolLogic<SignedTransaction>() {
        @Suspendable
        override fun call(): SignedTransaction {
            TODO()
        }
    }

    class UnacceptablePriceException(val givenPrice: Amount) : Exception()
    class AssetMismatchException(val expectedTypeName: String, val typeName: String) : Exception() {
        override fun toString() = "The submitted asset didn't match the expected type: $expectedTypeName vs $typeName"
    }

    class Buyer(val otherSide: SingleMessageRecipient,
                val timestampingAuthority: Party,
                val acceptablePrice: Amount,
                val typeToBuy: Class<out OwnableState>,
                val sessionID: Long) : ProtocolLogic<SignedTransaction>() {
        @Suspendable
        override fun call(): SignedTransaction {
            TODO()
        }
    }
}

Let’s unpack what this code does:

• It defines a several classes nested inside the main TwoPartyTradeProtocol singleton, and a couple of methods, one to run the buyer side of the protocol and one to run the seller side. Some of the classes are simply protocol messages.
• It defines the “trade topic”, which is just a string that namespaces this protocol. The prefix “platform.” is reserved by the DLG, but you can define your own protocols using standard Java-style reverse DNS notation.
• The runBuyer and runSeller methods take a number of parameters that specialise the protocol for this run, use them to construct a Buyer or Seller object respectively, and then add the new instances to the StateMachineManager. The purpose of this class is described below. The smm.add method takes a logger name as the first parameter, this is just a standard JDK logging identifier string, and the instance to add.

Going through the data needed to become a seller, we have:

• timestampingAuthority: LegallyIdentifiableNode - a reference to a node on the P2P network that acts as a trusted timestamper. The use of timestamping is described in Data model.
• otherSide: SingleMessageRecipient - the network address of the node with which you are trading.
• assetToSell: StateAndRef<OwnableState> - a pointer to the ledger entry that represents the thing being sold.
• price: Amount - the agreed on price that the asset is being sold for.
• myKeyPair: KeyPair - the key pair that controls the asset being sold. It will be used to sign the transaction.
• buyerSessionID: Long - a unique number that identifies this trade to the buyer. It is expected that the buyer knows that the trade is going to take place and has sent you such a number already. (This field may go away in a future iteration of the framework)

And for the buyer:

• acceptablePrice: Amount - the price that was agreed upon out of band. If the seller specifies a price less than or equal to this, then the trade will go ahead.
• typeToBuy: Class<out OwnableState> - the type of state that is being purchased. This is used to check that the sell side of the protocol isn’t trying to sell us the wrong thing, whether by accident or on purpose.
• sessionID: Long - the session ID that was handed to the seller in order to start the protocol.

The run methods return a ListenableFuture that will complete when the protocol has finished.

Alright, so using this protocol shouldn’t be too hard: in the simplest case we can just pass in the details of the trade to either runBuyer or runSeller, depending on who we are, and then call .get() on resulting object to block the calling thread until the protocol has finished. Or we could register a callback on the returned future that will be invoked when it’s done, where we could e.g. update a user interface.

Finally, we define a couple of exceptions, and two classes that will be used as a protocol message called SellerTradeInfo and SignaturesFromSeller.

Suspendable methods¶

The call method of the buyer/seller classes is marked with the @Suspendable annotation. What does this mean?

As mentioned above, our protocol framework will at points suspend the code and serialise it to disk. For this to work, any methods on the call stack must have been pre-marked as @Suspendable so the bytecode rewriter knows to modify the underlying code to support this new feature. A protocol is suspended when calling either receive, send or sendAndReceive which we will learn more about below. For now, just be aware that when one of these methods is invoked, all methods on the stack must have been marked. If you forget, then in the unit test environment you will get a useful error message telling you which methods you didn’t mark. The fix is simple enough: just add the annotation and try again.

The state machine manager¶

The SMM is a class responsible for taking care of all running protocols in a node. It knows how to register handlers with a MessagingService and iterate the right state machine when messages arrive. It provides the send/receive/sendAndReceive calls that let the code request network interaction and it will store a serialised copy of each state machine before it’s suspended to wait for the network.

To get a StateMachineManager, you currently have to build one by passing in a ServiceHub and a thread or thread pool which it can use. This will change in future so don’t worry about the details of this too much: just check the unit tests to see how it’s done.

Implementing the seller¶

Let’s implement the Seller.call method. This will be invoked by the platform when the protocol is started by the StateMachineManager.

val partialTX: SignedTransaction = receiveAndCheckProposedTransaction()

// These two steps could be done in parallel, in theory. Our framework doesn't support that yet though.
val ourSignature = signWithOurKey(partialTX)
val tsaSig = subProtocol(TimestampingProtocol(timestampingAuthority, partialTX.txBits))

val stx: SignedTransaction = sendSignatures(partialTX, ourSignature, tsaSig)

return stx

Here we see the outline of the procedure. We receive a proposed trade transaction from the buyer and check that it’s valid. Then we sign with our own key, request a timestamping authority to assert with another signature that the timestamp in the transaction (if any) is valid, and finally we send back both our signature and the TSA’s signature. Finally, we hand back to the code that invoked the protocol the finished transaction in a couple of different forms.

Let’s fill out the receiveAndCheckProposedTransaction() method.

@Suspendable
open fun receiveAndCheckProposedTransaction(): SignedTransaction {
    val sessionID = random63BitValue()

    // Make the first message we'll send to kick off the protocol.
    val hello = SellerTradeInfo(assetToSell, price, myKeyPair.public, sessionID)

    val maybeSTX = sendAndReceive<SignedTransaction>(TRADE_TOPIC, otherSide, buyerSessionID, sessionID, hello)

    maybeSTX.validate {
        // Check that the tx proposed by the buyer is valid.
        val missingSigs = it.verify(throwIfSignaturesAreMissing = false)
        if (missingSigs != setOf(myKeyPair.public, timestampingAuthority.identity.owningKey))
            throw SignatureException("The set of missing signatures is not as expected: $missingSigs")

        val wtx: WireTransaction = it.tx
        logger.trace { "Received partially signed transaction: ${it.id}" }

        checkDependencies(it)

        // This verifies that the transaction is contract-valid, even though it is missing signatures.
        serviceHub.verifyTransaction(wtx.toLedgerTransaction(serviceHub.identityService))

        if (wtx.outputs.sumCashBy(myKeyPair.public) != price)
            throw IllegalArgumentException("Transaction is not sending us the right amounnt of cash")

        // There are all sorts of funny games a malicious secondary might play here, we should fix them:
        //
        // - This tx may attempt to send some assets we aren't intending to sell to the secondary, if
        //   we're reusing keys! So don't reuse keys!
        // - This tx may include output states that impose odd conditions on the movement of the cash,
        //   once we implement state pairing.
        //
        // but the goal of this code is not to be fully secure (yet), but rather, just to find good ways to
        // express protocol state machines on top of the messaging layer.

        return it
    }
}

That’s pretty straightforward. We generate a session ID to identify what’s happening on the seller side, fill out the initial protocol message, and then call sendAndReceive. This function takes a few arguments:

• The topic string that ensures the message is routed to the right bit of code in the other side’s node.
• The session IDs that ensure the messages don’t get mixed up with other simultaneous trades.
• The thing to send. It’ll be serialised and sent automatically.
• Finally a type argument, which is the kind of object we’re expecting to receive from the other side.

Once sendAndReceive is called, the call method will be suspended into a continuation. When it gets back we’ll do a log message. The buyer is supposed to send us a transaction with all the right inputs/outputs/commands in return, with their cash put into the transaction and their signature on it authorising the movement of the cash.

You get back a simple wrapper class, UntrustworthyData<SignedTransaction>, which is just a marker class that reminds us that the data came from a potentially malicious external source and may have been tampered with or be unexpected in other ways. It doesn’t add any functionality, but acts as a reminder to “scrub” the data before use. Here, our scrubbing simply involves checking the signatures on it. Then we go ahead and check all the dependencies of this partial transaction for validity. Here’s the code to do that:

@Suspendable
private fun checkDependencies(stx: SignedTransaction) {
    // Download and check all the transactions that this transaction depends on, but do not check this
    // transaction itself.
    val dependencyTxIDs = stx.tx.inputs.map { it.txhash }.toSet()
    subProtocol(ResolveTransactionsProtocol(dependencyTxIDs, otherSide))
}

This is simple enough: we mark the method as @Suspendable because we’re going to invoke a sub-protocol, extract the IDs of the transactions the proposed transaction depends on, and then uses a protocol provided by the system to download and check them all. This protocol does a breadth-first search over the dependency graph, bottoming out at issuance transactions that don’t have any inputs themselves. Once the node has audited the transaction history, all the dependencies are committed to the node’s local database so they won’t be checked again next time.

After the dependencies, we check the proposed trading transaction for validity by running the contracts for that as well (but having handled the fact that some signatures are missing ourselves).

Here’s the rest of the code:

open fun signWithOurKey(partialTX: SignedTransaction) = myKeyPair.signWithECDSA(partialTX.txBits)

@Suspendable
open fun sendSignatures(partialTX: SignedTransaction, ourSignature: DigitalSignature.WithKey,
                        tsaSig: DigitalSignature.LegallyIdentifiable): SignedTransaction {
    val fullySigned = partialTX + tsaSig + ourSignature

    logger.trace { "Built finished transaction, sending back to secondary!" }

    send(TRADE_TOPIC, otherSide, buyerSessionID, SignaturesFromSeller(tsaSig, ourSignature))
    return fullySigned
}

It’s should be all pretty straightforward: here, txBits is the raw byte array representing the transaction.

In sendSignatures, we take the two signatures we calculated, then add them to the partial transaction we were sent. We provide an overload for the + operator so signatures can be added to a SignedTransaction easily. Finally, we wrap the two signatures in a simple wrapper message class and send it back. The send won’t block waiting for an acknowledgement, but the underlying message queue software will retry delivery if the other side has gone away temporarily.

Implementing the buyer¶

OK, let’s do the same for the buyer side:

@Suspendable
override fun call(): SignedTransaction {
    val tradeRequest = receiveAndValidateTradeRequest()
    val (ptx, cashSigningPubKeys) = assembleSharedTX(tradeRequest)
    val stx = signWithOurKeys(cashSigningPubKeys, ptx)
    val signatures = swapSignaturesWithSeller(stx, tradeRequest.sessionID)

    logger.trace { "Got signatures from seller, verifying ... "}
    val fullySigned = stx + signatures.timestampAuthoritySig + signatures.sellerSig
    fullySigned.verify()

    logger.trace { "Fully signed transaction was valid. Trade complete! :-)" }
    return fullySigned
}

@Suspendable
open fun receiveAndValidateTradeRequest(): SellerTradeInfo {
    // Wait for a trade request to come in on our pre-provided session ID.
    val maybeTradeRequest = receive<SellerTradeInfo>(TRADE_TOPIC, sessionID)

    maybeTradeRequest.validate {
        // What is the seller trying to sell us?
        val asset = it.assetForSale.state
        val assetTypeName = asset.javaClass.name
        logger.trace { "Got trade request for a $assetTypeName: ${it.assetForSale}" }

        // Check the start message for acceptability.
        check(it.sessionID > 0)
        if (it.price > acceptablePrice)
            throw UnacceptablePriceException(it.price)
        if (!typeToBuy.isInstance(asset))
            throw AssetMismatchException(typeToBuy.name, assetTypeName)

        // Check the transaction that contains the state which is being resolved.
        // We only have a hash here, so if we don't know it already, we have to ask for it.
        subProtocol(ResolveTransactionsProtocol(setOf(it.assetForSale.ref.txhash), otherSide))

        return it
    }
}

@Suspendable
open fun swapSignaturesWithSeller(stx: SignedTransaction, theirSessionID: Long): SignaturesFromSeller {
    logger.trace { "Sending partially signed transaction to seller" }

    // TODO: Protect against the seller terminating here and leaving us in the lurch without the final tx.

    return sendAndReceive(TRADE_TOPIC, otherSide, theirSessionID, sessionID, stx, SignaturesFromSeller::class.java).validate { it }
}

open fun signWithOurKeys(cashSigningPubKeys: List<PublicKey>, ptx: TransactionBuilder): SignedTransaction {
    // Now sign the transaction with whatever keys we need to move the cash.
    for (k in cashSigningPubKeys) {
        val priv = serviceHub.keyManagementService.toPrivate(k)
        ptx.signWith(KeyPair(k, priv))
    }

    return ptx.toSignedTransaction(checkSufficientSignatures = false)
}

open fun assembleSharedTX(tradeRequest: SellerTradeInfo): Pair<TransactionBuilder, List<PublicKey>> {
    val ptx = TransactionBuilder()
    // Add input and output states for the movement of cash, by using the Cash contract to generate the states.
    val wallet = serviceHub.walletService.currentWallet
    val cashStates = wallet.statesOfType<Cash.State>()
    val cashSigningPubKeys = Cash().generateSpend(ptx, tradeRequest.price, tradeRequest.sellerOwnerKey, cashStates)
    // Add inputs/outputs/a command for the movement of the asset.
    ptx.addInputState(tradeRequest.assetForSale.ref)
    // Just pick some new public key for now. This won't be linked with our identity in any way, which is what
    // we want for privacy reasons: the key is here ONLY to manage and control ownership, it is not intended to
    // reveal who the owner actually is. The key management service is expected to derive a unique key from some
    // initial seed in order to provide privacy protection.
    val freshKey = serviceHub.keyManagementService.freshKey()
    val (command, state) = tradeRequest.assetForSale.state.withNewOwner(freshKey.public)
    ptx.addOutputState(state)
    ptx.addCommand(command, tradeRequest.assetForSale.state.owner)

    // And add a request for timestamping: it may be that none of the contracts need this! But it can't hurt
    // to have one.
    ptx.setTime(Instant.now(), timestampingAuthority, 30.seconds)
    return Pair(ptx, cashSigningPubKeys)
}

This code is longer but still fairly straightforward. Here are some things to pay attention to:

1. We do some sanity checking on the received message to ensure we’re being offered what we expected to be offered.
2. We create a cash spend in the normal way, by using Cash().generateSpend. See the contracts tutorial if this isn’t clear.
3. We access the service hub when we need it to access things that are transient and may change or be recreated whilst a protocol is suspended, things like the wallet or the timestamping service. Remember that a protocol may be suspended when it waits to receive a message across node or computer restarts, so objects representing a service or data which may frequently change should be accessed ‘just in time’.
4. Finally, we send the unfinished, invalid transaction to the seller so they can sign it. They are expected to send back to us a SignaturesFromSeller, which once we verify it, should be the final outcome of the trade.

As you can see, the protocol logic is straightforward and does not contain any callbacks or network glue code, despite the fact that it takes minimal resources and can survive node restarts.

Progress tracking¶

Not shown in the code snippets above is the usage of the ProgressTracker API. Progress tracking exports information from a protocol about where it’s got up to in such a way that observers can render it in a useful manner to humans who may need to be informed. It may be rendered via an API, in a GUI, onto a terminal window, etc.

A ProgressTracker is constructed with a series of Step objects, where each step is an object representing a stage in a piece of work. It is therefore typical to use singletons that subclass Step, which may be defined easily in one line when using Kotlin. Typical steps might be “Waiting for response from peer”, “Waiting for signature to be approved”, “Downloading and verifying data” etc.

Each step exposes a label. By default labels are fixed, but by subclassing RelabelableStep you can make a step that can update its label on the fly. That’s useful for steps that want to expose non-structured progress information like the current file being downloaded. By defining your own step types, you can export progress in a way that’s both human readable and machine readable.

Progress trackers are hierarchical. Each step can be the parent for another tracker. By altering the ProgressTracker.childrenFor[step] = tracker map, a tree of steps can be created. It’s allowed to alter the hierarchy at runtime, on the fly, and the progress renderers will adapt to that properly. This can be helpful when you don’t fully know ahead of time what steps will be required. If you _do_ know what is required, configuring as much of the hierarchy ahead of time is a good idea, as that will help the users see what is coming up.

Every tracker has not only the steps given to it at construction time, but also the singleton ProgressTracker.UNSTARTED step and the ProgressTracker.DONE step. Once a tracker has become DONE its position may not be modified again (because e.g. the UI may have been removed/cleaned up), but until that point, the position can be set to any arbitrary set both forwards and backwards. Steps may be skipped, repeated, etc. Note that rolling the current step backwards will delete any progress trackers that are children of the steps being reversed, on the assumption that those subtasks will have to be repeated.

Trackers provide an Rx observable which streams changes to the hierarchy. The top level observable exposes all the events generated by its children as well. The changes are represented by objects indicating whether the change is one of position (i.e. progress), structure (i.e. new subtasks being added/removed) or some other aspect of rendering (i.e. a step has changed in some way and is requesting a re-render).

The protocol framework is somewhat integrated with this API. Each ProtocolLogic may optionally provide a tracker by overriding the protocolTracker property (getProtocolTracker method in Java). If the ProtocolLogic.subProtocol method is used, then the tracker of the sub-protocol will be made a child of the current step in the parent protocol automatically, if the parent is using tracking in the first place. The framework will also automatically set the current step to DONE for you, when the protocol is finished.

Because a protocol may sometimes wish to configure the children in its progress hierarchy _before_ the sub-protocol is constructed, for sub-protocols that always follow the same outline regardless of their parameters it’s conventional to define a companion object/static method (for Kotlin/Java respectively) that constructs a tracker, and then allow the sub-protocol to have the tracker it will use be passed in as a parameter. This allows all trackers to be built and linked ahead of time.

In future, the progress tracking framework will become a vital part of how exceptions, errors, and other faults are surfaced to human operators for investigation and resolution.