High-Coverage, Unbounded Sound Predictive Race Detection
Dynamic program analysis can predict data races knowable from an observed execution, but existing predictive analyses either miss races or cannot analyze full program executions. This paper presents Vindicator, a novel, sound (no false races) predictive approach that finds more data races than existing predictive approaches. Vindicator achieves high coverage by using a new, efficient analysis that finds all possible predictable races but may detect false races. Vindicator ensures soundness using a novel algorithm that checks each potential race to determine whether it is a true predictable race. An evaluation using large Java programs shows that Vindicator finds hard-to-detect predictable races that existing sound predictive analyses miss, at a comparable performance cost.
Thu 21 Jun Times are displayed in time zone: Eastern Time (US & Canada) change
14:00 - 15:40: Concurrency DebuggingPLDI Research Papers at Grand Ballroom AB Chair(s): Tony HoskingAustralian National University / Data61 | |||
14:00 - 14:25 Talk | iReplayer: In-situ and Identical Record-and-Replay for Multithreaded Applications PLDI Research Papers Hongyu LiuUniversity of Texas at San Antonio, USA, Sam SilvestroUniversity of Texas at San Antonio, USA, Wei WangUniversity of Texas at San Antonio, USA, Chen TianHuawei Lab, USA, Tongping Liu Media Attached | ||
14:25 - 14:50 Talk | D4: Fast Concurrency Debugging with Parallel Differential Analysis PLDI Research Papers Media Attached | ||
14:50 - 15:15 Talk | High-Coverage, Unbounded Sound Predictive Race Detection PLDI Research Papers Jake RoemerOhio State University, Kaan GençOhio State University, USA, Michael D. BondOhio State University Media Attached | ||
15:15 - 15:40 Talk | CURD: A Dynamic CUDA Race Detector PLDI Research Papers Media Attached |