An Empirical Study of Data Race Detector Tools

The industry of software applications has been increased significantly because of the high demand of using the software applications. This revolution leads on developing many concurrent software systems. Noticeably, some of these concurrent software systems have falsely report data race condition to one or more of their shared variables. Debugging such concurrent software systems to find the race condition is a challenge, especially for large and complex software systems. Since the race condition concerned mostly ignored in the concurrent software systems, adopting it could help to ensure the efficiency of these software systems. There are few detector tools that have been known in the industry focusing on data race detectors. This paper aims to study those tools. We are going to conduct empirical study of data race using well known tools in order to measure the correctness, performances and effectiveness of those tools in practical by using some benchmarks. Those benchmarks will be tested on each tool and compare it with others to see the similarity and differentiate.