Deductive Verification of Parallel Programs Using Why3

The Message Passing Interface specification (MPI) defines a portable message-passing API used to program parallel computers. MPI programs manifest a number of challenges on what concerns correctness: sent and expected values in communications may not match, resulting in incorrect computations possibly leading to crashes; and programs may deadlock resulting in wasted resources. Existing tools are not completely satisfactory: model-checking does not scale with the number of processes; testing techniques wastes resources and are highly dependent on the quality of the test set. As an alternative, we present a prototype for a type-based approach to programming and verifying MPI like programs against protocols. Protocols are written in a dependent type language designed so as to capture the most common primitives in MPI, incorporating, in addition, a form of primitive recursion and collective choice. Protocols are then translated into Why3, a deductive software verification tool. Source code, in turn, is written in WhyML, the language of the Why3 platform, and checked against the protocol. Programs that pass verification are guaranteed to be communication safe and free from deadlocks. We verified several parallel programs from textbooks using our approach, and report on the outcome.Comment: In Proceedings ICE 2015, arXiv:1508.0459

Pabble: parameterised Scribble

© 2014, The Author(s).Many parallel and distributed message-passing programs are written in a parametric way over available resources, in particular the number of nodes and their topologies, so that a single parallel program can scale over different environments. This article presents a parameterised protocol description language, Pabble, which can guarantee safety and progress in a large class of practical, complex parameterised message-passing programs through static checking. Pabble can describe an overall interaction topology, using a concise and expressive notation, designed for a variable number of participants arranged in multiple dimensions. These parameterised protocols in turn automatically generate local protocols for type checking parameterised MPI programs for communication safety and deadlock freedom. In spite of undecidability of endpoint projection and type checking in the underlying parameterised session type theory, our method guarantees the termination of end point projection and type checking

Protocol-based verification of message-passing parallel programs

© 2015 ACM.We present ParTypes, a type-based methodology for the verification of Message Passing Interface (MPI) programs written in the C programming language. The aim is to statically verify programs against protocol specifications, enforcing properties such as fidelity and absence of deadlocks. We develop a protocol language based on a dependent type system for message-passing parallel programs, which includes various communication operators, such as point-to-point messages, broadcast, reduce, array scatter and gather. For the verification of a program against a given protocol, the protocol is first translated into a representation read by VCC, a software verifier for C. We successfully verified several MPI programs in a running time that is independent of the number of processes or other input parameters. This contrasts with alternative techniques, notably model checking and runtime verification, that suffer from the state-explosion problem or that otherwise depend on parameters to the program itself. We experimentally evaluated our approach against state-of-the-art tools for MPI to conclude that our approach offers a scalable solution

Differentially Testing Soundness and Precision of Program Analyzers

In the last decades, numerous program analyzers have been developed both by academia and industry. Despite their abundance however, there is currently no systematic way of comparing the effectiveness of different analyzers on arbitrary code. In this paper, we present the first automated technique for differentially testing soundness and precision of program analyzers. We used our technique to compare six mature, state-of-the art analyzers on tens of thousands of automatically generated benchmarks. Our technique detected soundness and precision issues in most analyzers, and we evaluated the implications of these issues to both designers and users of program analyzers