Abstract
In this paper we present the OpenMP Analysis Toolkit (OAT), which uses Satisfiability Modulo Theories (SMT) solver based symbolic analysis to detect data races and deadlocks in OpenMP codes. Our approach approximately simulates real executions of an OpenMP program through schedule permutation. We conducted experiments on real-world OpenMP benchmarks and student homework assignments by comparing our OAT tool with two commercial dynamic analysis tools: Intel Thread Checker and Sun Thread Analyzer, and one commercial static analysis tool: Viva64 PVS Studio. The experiments show that our symbolic analysis approach is more accurate than static analysis and more efficient and scalable than dynamic analysis tools with less false positives and negatives.
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