D4: Fast Concurrency Debugging with Parallel Differential Analysis
We present D4, a fast concurrency analysis framework that detects concurrency bugs (e.g., data races and deadlocks) interactively in the programming phase. As developers add, modify, and remove statements, the code changes are sent to D4 to detect concurrency bugs in real time, which in turn provides immediate feedback to the developer of the new bugs. The cornerstone of D4 includes a novel system design and two novel parallel differential algorithms that embrace both change and parallelization for fundamental static analyses of concurrent programs. Both algorithms react to program changes by memoizing the analysis results and only recomputing the impact of a change in parallel. Our evaluation on an extensive collection of large real-world applications shows that D4 efficiently pinpoints concurrency bugs within 100ms on average after a code change, several orders of magnitude faster than both the exhaustive analysis and the state-of-the-art incremental techniques.
Thu 21 JunDisplayed time zone: Eastern Time (US & Canada) change
14:00 - 15:40 | Concurrency DebuggingPLDI Research Papers at Grand Ballroom AB Chair(s): Tony Hosking Australian National University / Data61 | ||
14:00 25mTalk | iReplayer: In-situ and Identical Record-and-Replay for Multithreaded Applications PLDI Research Papers Hongyu Liu University of Texas at San Antonio, USA, Sam Silvestro University of Texas at San Antonio, USA, Wei Wang University of Texas at San Antonio, USA, Chen Tian Huawei Lab, USA, Tongping Liu Media Attached | ||
14:25 25mTalk | D4: Fast Concurrency Debugging with Parallel Differential Analysis PLDI Research Papers Media Attached | ||
14:50 25mTalk | High-Coverage, Unbounded Sound Predictive Race Detection PLDI Research Papers Jake Roemer Ohio State University, Kaan Genç Ohio State University, USA, Michael D. Bond Ohio State University Media Attached | ||
15:15 25mTalk | CURD: A Dynamic CUDA Race Detector PLDI Research Papers Media Attached |