Refinement of structural heuristics for model checking of concurrent programs through data mining

Detecting concurrency bugs in multi-threaded programs through model-checking is complicated by the combinatorial explosion in the number of ways that different threads can be interleaved to produce different combinations of behaviors. At the same time, concurrency bugs tend to be limited in their scope and scale due to the way in which concurrent programs are designed, and making visible the rules that govern the relationships between threads can help us to better identify which interleavings are worth investigating. In this work, patterns of read-write sequences are mined from a single execution of the target program to produce a quantitative, categorical model of thread behaviors. This model is exploited by a novel structural heuristic. Experiments with a proof-of-concept implementation, built using Java Pathfinder and WEKA, demonstrate that this heuristic locates bugs faster and more reliably than a conventional counterpart. HighlightsThe paper explores how model checking can be hybridized with trace analysis.Traces are mined to produce a categorical model of thread behavior.A heuristic for race detection is retrofitted to exploit the behavior model.With proper parameterization, the novel heuristic finds bugs 8× faster.A novel mutation-based benchmark generation process is introduced for validation.