Compositional verification of embedded real-time systems
نویسندگان
چکیده
In an embedded real-time system (ERTS), tasks (software) are typically executed on a multicore shared-memory platform (hardware). The number of cores is usually small, contrasted with larger complex that share data to collaborate. Since most ERTSs safety-critical, it crucial rigorously verify their software against various requirements under the actual hardware constraints (concurrent access data, cores). Both systems and formal methods communities provide elegant techniques realize such verification, which nevertheless face major challenges. For instance, model checking (formal methods) suffers from state-space explosion problem, whereas schedulability analysis (real-time systems) pessimistic restricted simple task models properties. this paper, we propose scalable generic approach formally ERTSs. core contribution enabling, through joining forces both communities, compositional verification tame size. To end, formalize realistic ERTS where arbitrary jobs job segments, then show possible, using hybrid (from communities), state-of-the-art partitioned fixed-priority (P-FP) limited preemption scheduling algorithm. consists following steps, given above First, compute fine-grained sharing overheads for each segment reads or writes some shared memory. Second, generalize algorithm that, aware overheads, computes affinity (task-core allocation) guaranteeing hard-real-time (HRT) tasks. Third, devise timed automata (TA) ERTS, takes into account affinity, algorithm, demonstrate properties can be verified compositionally, i.e., subset instead whole therefore reducing particular, enable computation tight worst-case response times (WCRTs) other bounds separating events different cores, thus overcoming pessimism techniques. We fully automate our its benefits three real-world ERTSs, namely two autonomous robots automotive case study WATERS 2017 industrial challenge.
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ژورنال
عنوان ژورنال: Journal of Systems Architecture
سال: 2023
ISSN: ['1383-7621', '1873-6165']
DOI: https://doi.org/10.1016/j.sysarc.2023.102928