Static Race Detection for Periodic Programs
PROGRAMMING LANGUAGES AND SYSTEMS, ESOP 2022(2022)
Abstract
We consider the problem of statically detecting data races in periodic real-time programs that use locks, and run on a single processor platform. We propose a technique based on a small set of rules that exploits the priority, periodicity, locking, and timing information of tasks in the program. One of the key requirements is a response time analysis for such programs, and we propose an algorithm to compute this for the case of non-nested locks. We have implemented our analysis for real-time programs written in C in a tool called PePRacer and evaluated its performance on a small set of benchmarks from the literature.
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Key words
Real-Time systems,periodic programs,static analysis,data races,WCRT Analysis
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