2026-07-26T16:58:48Z https://drops.dagstuhl.de/oai

oai:drops-oai.dagstuhl.de:13298 2024-03-06T10:52:03Z ddc:004 open_access

Static Race Detection for RTOS Applications Tulsyan, Rishi Pai, Rekha D'Souza, Deepak Static analysis concurrency data-race detection RTOS We present a static analysis technique for detecting data races in Real-Time Operating System (RTOS) applications. These applications are often employed in safety-critical tasks and the presence of races may lead to erroneous behaviour with serious consequences. Analyzing these applications is challenging due to the variety of non-standard synchronization mechanisms they use. We propose a technique based on the notion of an "occurs-in-between" relation between statements. This notion enables us to capture the interplay of various synchronization mechanisms. We use a pre-analysis and a small set of not-occurs-in-between patterns to detect whether two statements may race with each other. Our experimental evaluation shows that the technique is efficient and effective in identifying races with high precision. Schloss Dagstuhl – Leibniz-Zentrum für Informatik Rishi Tulsyan and Rekha Pai and Deepak D'Souza 2020 Is Part Of LIPIcs, Volume 182, 40th IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS 2020) InProceedings Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/LIPIcs.FSTTCS.2020.57 urn:nbn:de:0030-drops-132983 https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.FSTTCS.2020.57 eng https://creativecommons.org/licenses/by/3.0/legalcode