Abstract

Dataflow analyses for concurrent programs differ from their singlethreaded counterparts in that they must account for shared memory locations being overwritten by concurrent threads. Existing dataflow analysis techniques for concurrent programs typically fall at either end of a spectrum: at one end, the analysis conservatively kills facts about all data that might possibly be shared by multiple threads; at the other end, a precise thread-interleaving analysis determines which data may be shared, and thus which dataflow facts must be invalidated. The former approach can suffer from imprecision, whereas the latter does not scale. We present RADAR, a framework that automatically converts a dataflow analysis for sequential programs into one that is correct for concurrent programs. RADAR uses a race detection engine to kill the dataflow facts, generated and propagated by the sequential

Citations