Asynchronous message passing systems are fast becoming a common means for communication between devices. Two problems existing in message passing programs are difficult to solve. The first problem, intended or otherwise, is message-race where a receive may match with more than one send in the runtime system. This non-determinism often leads to intermittent and unexpected behavior depending on the resolution of the race. Another problem is deadlock, which is a situation in that each member process of the group is waiting for some member process to communicate with it, but no member is attempting to communicate with it. Detecting if message-race and/or deadlocks exist in a message passing program are both NP-complete. The difficulty of solving the two problems also comes from three factors that complicate the semantics: asynchronous communication, synchronous barrier, and buffering settings including infinite buffering (the system can buffer messages) and zero buffering (the system has no internal buffering). To solve the above problems with complicating factors, this research provides a novel predictive analysis that initializes a concrete execution and then predicts the behavior of other executions that arise from the initial execution. This research starts with Satisfiability Modulo Theories (SMT) based model checking that provides precise analysis for the program behavior. Unfortunately, a precise analysis using SMT does not scale to large programs. As such, the SMT based model checking is combined with heuristic search for witnessing program properties. The heuristic search is efficient in identifying how sends may match with receives in the runtime as it only looks for the match relations for sends and receives in a small searching space initially; the space is increased only if the program property is not witnessed, until all possible match relations for sends and receives reflected in message non-determinism are found. This research also gives a static analysis approach that is scalable as it does not need to analyze the full set of program behaviors; rather, the static analysis only uses polynomial-time algorithms to identify all potential deadlocks in a send-receive templates given a set of pre-defined deadlock patterns. Given the predictive analysis consisting of SMT based model checking with heuristic search and static analysis, this research is able to solve the two problems above. The work in this dissertation also demonstrates that the predictive analysis is more efficient than the existing tools for verifying message passing programs.
College and Department
Physical and Mathematical Sciences; Computer Science
BYU ScholarsArchive Citation
Huang, Yu, "An Analyzer for Message Passing Programs" (2016). All Theses and Dissertations. 5865.
Message passing, MPI, MCAPI, SMT, Static analysis, Model checking