Data Race Detection on Compressed Traces

TL;DR

This paper introduces algorithms for detecting data races directly on compressed program traces using straight line programs, enabling faster analysis by avoiding decompression.

Contribution

It presents novel linear-time algorithms for data race detection on compressed traces using happens-before and lockset methods, improving efficiency over traditional approaches.

Findings

Algorithms run in linear time relative to compressed trace size

Significant speedups observed in experiments on standard benchmarks

Effective detection of data races directly on compressed data

Abstract

We consider the problem of detecting data races in program traces that have been compressed using straight line programs (SLP), which are special context-free grammars that generate exactly one string, namely the trace that they represent. We consider two classical approaches to race detection --- using the happens-before relation and the lockset discipline. We present algorithms for both these methods that run in time that is linear in the size of the compressed, SLP representation. Typical program executions almost always exhibit patterns that lead to significant compression. Thus, our algorithms are expected to result in large speedups when compared with analyzing the uncompressed trace. Our experimental evaluation of these new algorithms on standard benchmarks confirms this observation.