Scalable Thread Sharing Analysis

Abstract

We present two scalable algorithms for identifying program locations that access thread-shared data in concurrent programs. The static algorithm, though simple, and without performing the expensive whole program information flow analysis, is much more efficient, less memory-demanding, and even more precise than the classical escape analysis algorithm. The dynamic algorithm, powered by a location- based approach, achieves significant runtime speedups over a precise dynamic escape analysis. Our evaluation on a set of large real world complex multithreaded systems such as Apache Derby and Eclipse shows that our algorithms achieve unprecedented scalability. Used by client applications, our algorithms reduce the recording overhead of a record-replay system by 9X on average (as much as 16X) and increase the runtime logging speed of a data race detector by 32% on average (as much as 52%).