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Sound and Precise Analysis of Parallel Programs through Schedule Specialization

By Jingyue Wu, Yang Tang, Gang Hu, Heming Cui and Junfeng Yang

Abstract

Parallel programs are known to be difficult to analyze. A key reason is that they typically have an enormous number of execution interleavings, or schedules. Static analysis over all schedules requires over-approximations, resulting in poor precision; dynamic analysis rarely covers more than a tiny fraction of all schedules. We propose an approach called schedule specialization to analyze a parallel program over only a small set of schedules for precision, and then enforce these schedules at runtime for soundness of the static analysis results. We build a schedule specialization framework for C/C++ multithreaded programs that use Pthreads. Our framework avoids the need to modify every analysis to be schedule-aware by specializing a program into a simpler program based on a schedule, so that the resultant program can be analyzed with stock analyses for improved precision. Moreover, our framework provides a precise schedule-aware def-use analysis on memory locations, enabling us to build three highly precise analyses: an alias analyzer, a data-race detector, and a path slicer. Evaluation on 17 programs, including 2 real-world programs and 15 popular benchmarks, shows that analyses using our framework reduced may-aliases by 61.9%, false race reports by 69%, and path slices by 48.7%; and detected 7 unknown bugs in well-checked programs

Topics: Algorithms, Design, Reliability, Verification Keywords Specialization, parallel programs, multithreading, control-flow analysis
Year: 2012
DOI identifier: 10.1145/2345156.2254090
OAI identifier: oai:CiteSeerX.psu:10.1.1.227.4859
Provided by: CiteSeerX
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