Randomized trial develops an algorithm to detect data races in multithreaded applications, suggesting improvements for software reliability.
Most critical software developed today relies on multiple threads, a technique that is notoriously difficult to implement correctly. This complexity often leads to concurrency-related bugs, such as data races. Furthermore, emerging trends in robotics and unmanned vehicle software add further complications. These systems are not only multi threaded but also interact with hardware, require specific OS environments, utilize IPC, and demand rigorous testing. In this paper, we build upon a multi core version of S2E to present an algorithm devised to better detect data races in these complex environments. To do so, we leverage S2E’s full-system emulation, its plugin infrastructure, and our custom CPU core scheduler.
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Kutovoi et al. (2026) studied this question.
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