Synchronizability for Verification of Asynchronously Communicating Systems Samik

Synchronizability for Verification of Asynchronously Communicating Systems Samik Basu Iowa State University Tevfik Bultan University of California at Santa Barbara Meriem Ouederni University of Malaga

Asynchronously Communicating Systems • Message-based asynchronous communication has been adopted in many domains: – Web service composition • Interacting component services • Java API for XML Messaging (JAXM) – Distributed programming • Interacting distributed programs • Erlang – System programming • Interacting processes • Singularity OS, Go programming language

Asynchronous Messaging • Sender does not have to wait for the receiver – Message is inserted to a message queue – Messaging platform guarantees the delivery of the message • Why support asynchronous messaging? – Otherwise the sender has to block and wait for the receiver – Sender may not need any data to be returned – If the sender needs some data to be returned, it should only wait when it needs to use that data – Asynchronous messaging can alleviate the latency of message transmission – Asynchronous messaging can prevent sender from blocking if the receiver service is temporarily unavailable • Rather then creating a thread to handle the send, use asynchronous messaging

Objective & Challenge • Automatic verification of desired properties of asynchronous systems • Asynchronous communication is hard to analyze – Systems can have infinite-state spaces due to message queues – Asynchronously communicating finite state machines can simulate Turing Machines – In general, automated verification of asynchronously communicating finite state machines is undecidable

Motivation: Singularity OS • Experimental OS developed by Microsoft Research to explore new ideas for operating system design • Key design principles: – Dependability – Security • Key architectural decision: – Implement a sealed process system • Software Isolated Processes (SIPs) – Closed code space (no dynamic code loading or code generation) – Closed object space (no shared memory) • Inter-process communication occurs via asynchronous message passing over channels

Singularity Channels • Channels allow 2 -Party asynchronous communication via FIFO message queues – Sends are non blocking – Receives block until a message is at the head of a receive queue • Each channel has exactly two endpoints – Type exposed for each endpoint (Exp and Imp) – Each endpoint owned by at most one process at any time • Owner of Exp referred to as Server • Owner of Imp referred to as Client

Channel Contracts • Written in Sing # • Contracts specify two things: 1. The messages that may be sent over a channel • out message are sent from the Server endpoint to the Client endpoint (S C) • in messages are sent from the Client endpoint to the Server endpoint (C S) – public contract Keyboard. Device. Contract { out message Ack. Key( uint key ); out message Nak. Key(); out message Success(); in message Get. Key(); in message Poll. Key(); state Start { Success! -> Ready; } state Ready { Get. Key? -> Waiting; Poll. Key? -> (Ack. Key! or Nak. Key!) -> Ready; } The set of allowed message sequences • out message marked with ! • in messages marked with ? state Waiting { Ack. Key! -> Ready; Nak. Key! -> Ready; } }

Channel Contracts • A contract specifies a finite state machine • Each message causes a transition from one state to another state public contract Keyboard. Device. Contract { Keyboard. Device. Contract out message Ack. Key( uint key ); out message Nak. Key(); out message Success(); in message Get. Key(); in message Poll. Key(); Start S C: Ack. Key S C: Success Ready S C: Nak. Key state Start { Implicit Success! -> Ready; State } C S: Poll. Key C S: Get. Key Waiting S C: Ack. Key Ready$0 S C: Ack. Key state Ready { Get. Key? -> Waiting; Poll. Key? -> (Ack. Key! or Nak. Key!) -> Ready; } state Waiting { Ack. Key! -> Ready; Nak. Key! -> Ready; } }

Singularity Channel Contract Verification • Singularity compiler automatically checks compliance of client and server processes to the specified contract • Claim from Singularity documentation: – "clients and servers that have been verified separately against the same contract C are guaranteed not to deadlock when allowed to communicate according to C. “ • This claim is wrong!

Bad Things Can Happen: The Tpm. Contract Server Ready. State$0 Send? Server Receive Queue Ack. Start. Send! Send. Complete! Tpm. Status! Get. Tpm. Status Send Ready. State IO_RUNNING Get. Tpm. Status? Ready. State$1 IO_RUNNING$0 Tpm. Status! Stuck! Client Ready. State$0 Send! Client Receive Queue Ack. Start. Send? Send. Complete? Tpm. Status? Send. Complete Ack. Start. Send Ready. State IO_RUNNING Get. Tpm. Status! Ready. State$1 IO_RUNNING$0 Tpm. Status? Send Sequence C S: S C: Send Ack. Start. Send. Complete Get. Tpm. Status

Properties we may want to verify • It would be nice if we can verify properties about channel contracts such as: – After each Send. Complete message is sent, eventually a Send or Get. Tpm. Status message is sent – The processes can reach the Ready. State with empty message queues after the Send. Complete and Get. Tpm. Status messages are sent

Our Approach • We know that verifying properties of asynchronously communicating systems is difficult due to message queues – Model checking such systems is undecidable even for finite state process models if the message queues are unbounded • We ask the following question: – Can we identify asynchronously communicating systems where asynchronous communication does not create new behaviors? • We call such systems synchronizable

Verification via Synchronizability • If a system is synchronizable, then – behaviors of the system remain the same if we replace asynchronous communication with synchronous communication Synchronizable asynchronous behaviors = synchronous behaviors • If a system is synchronizable, then – we can verify the synchronous version of the system finite state processes + synchronous communication = finite state system Synchronizable verification results for asynchronous system = verification results for synchronous system

Equivalence of what type of behaviors? Synchronizability in terms of – Sequences of send actions • Receive actions are considered local to the processes and their ordering is not taken into account – Reachability of states with no pending receives (we call such states synchronized states) • States with pending receives imply some process has not yet reacted to messages sent to it, so the reachability of states where the messages queues are not empty are not taken into account

Three Examples, Example 1 !e ? a 1 ? e ? a 2 !r 1 !r 2 requester !a 1 !a 2 ? r 1 ? r 2 server • Sequences of send actions are identical for both asynchronous and synchronous versions: (r 1 a 1 | r 2 a 2)* e • During all executions the message queues use a fixed amount of space

Example 2 !e ? a 1 ? a 2 !r 1 !r 2 requester ? e !a 1 !a 2 ? r 1 ? r 2 server • Sequences of send actions for the asynchronous version is not a regular set and is not same as the synchronous version • Queues can grow arbitrarily large

Example 3 !e !r 2 !r 1 ? a !r requester ? r 1 !a ? e ? r 2 ? r server • Sequences of send actions are identical for synchronous and asynchronous versions: (r 1 | r 2 | ra)* e • Queues can grow arbitrarily large

# of states in thousands State Spaces of the Three Examples queue length • Verification of Examples 2 and 3 are difficult even if we bound the queue length • Example 1 is synchronizable • Example 2 is not synchronizable • Example 3 is synchronizable, so it can be verified efficiently!

Contributions of this paper Synchronizability definition in terms of – Sequences of send actions – Reachability of states with no pending receives, i. e. , synchronized states • Necessary and sufficient condition for this definition of synchronizability • Implementation and experiments on the Singularity channel contracts

Main Result I 0 : Synchronous System (0 size message queue) Ik: Bounded Asynchronous System (k size message queue) I : Asynchronous System (unbounded queue) I 0 equivalent to I 1 iff Ik equivalent to I Equivalence is defined as: Identical set of send sequences and identical reachability of synchronized states

Earlier Result I 0 equivalent to I 1 iff Ik equivalent to I When equivalence is defined as: Identical set of send sequences Above condition was proved in an earlier paper: “Choreography Conformance via Synchronizability” [Basu and Bultan WWW’ 11] In this paper we extend this earlier result by also considering reachability of synchronized states

Proof Summary • Assume I 0 and I 1 are equivalent • Assume for some k: Ik has some synchronized trace absent in I 1 or I 0 • Show contradiction

Proof Summary • Assume I 0 and I 1 are equivalent • Assume for some k: Ik has some synchronized trace absent in I 1 or I 0 • Case 1: There exists a new reachable synchronized state that differs from a prior one in exactly one local state – Proof by contradiction leveraging the fact that I 0 and I 1 are equivalent

Proof Summary • Assume I 0 and I 1 are equivalent • Assume for some k: Ik has some synchronized trace absent in I 1 or I 0 • Case 1: There exists a new reachable synchronized state that differs from a prior one in exactly one local state – Proof by contradiction leveraging the fact that I 0 and I 1 are equivalent • Case 2: There exists a new reachable synchronized state that differs from a prior one in more that one local state – Proof by contradiction leveraging Case 1

Implementation • Implemented using CADP toolbox for checking synchronizability of Singularity Channel Contracts • We used the front end of an earlier tool called Tune for analyzing Singularity channel contracts [Stengel, Bultan ISSTA 2009] • We generate Lotos specifications for synchronized (I 0) and 1 -boundedasynchronous (I 0) versions of the system • Then we use the equivalence checking algorithms implemented in CADP toolbox to check their equivalence • Using Tune, we can also generate Promela specifications for synchronized (I 0) version which can then be used for model checking behaviors of synchronizable channel contracts

Experimental Results • Checked synchronizability of 86 Singularity Channel Contracts – Synchronous Systems: 2 to 23 states; 1 to 60 transitions – Asynchronous System with buffer size 1: 3 to 99 states; 2 to 136 transitions • We first construct and reduce the synchronous and 1 -bounded asynchronous systems (takes about 10 secs on average) and then do the equivalence checking (takes about 3 secs on average) • 84 Contracts are synchronizable • 2 contracts that are not synchronizable cause deadlocks! – i. e. , they are buggy!

Related Work Synchronizability defined only in terms of equivalence of send action sequences: • [Fu et al. TSE’ 05]: Sufficient conditions for synchronizability to verify asynchronously communicating Web services – Similar sufficient conditions in [Honda et al. POPL’ 08] for session types • [Basu and Bultan WWW’ 11]: Necessary and sufficient condition for synchronizability

Related Work Restricted Asynchronous Communication: • [Cece, Finkel Info. & Comp’ 05]: Reachability properties for half-duplex systems – At most one participating process has pending messages to be consumed • [Torre et al. TACAS’ 08]: Verification of asynchronous systems with restricted communication topologies (e. g. , tree)

Related Work Slack elasticity [Manohar, Martin MPC 98] • Presents conditions under which changing the size of communication queues does not effect the behavior of the system • Behavior definition also takes the decision points into account in addition to message sequences – does not consider the synchronized states • It gives sufficient conditions for slack elasticity and discusses how to construct systems to ensure slack elasticity

Related Work • Singularity: – [Hunt, Larus SIGOPS ‘ 07] Singularity: rethinking the software stack – [Fähndrich, Aiken, Hawblitzel, et. al SIGOPS/Eurosys ‘ 07] Language support for fast and reliable message-based communication in singularity os. – Influenced by work on Session Types • [Honda, Vasconcelos, Kubo ESOP ’ 98] Language primitives and type discipline for structured communication-based programming – Source code and RDK: http: //codeplex. com/singularity

Related Work • Synchronizability is also related to choreography realizability problem: – [Fu, Bultan, Su TCS’ 04] – [Kazhamiakin, Pistore FORTE’ 06] – [Lohmann, Wolf ICSOC’ 11] – [Basu, Bultan, Ouderni POPL’ 12]

Future Directions • Beyond FIFO communication – out-of-order consumption of messages – unreliable messaging • Beyond FSM for behavioral modeling – Synchronizability of programs modeld as push-down systems • Apply to different languages

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