BMC for Weak Memory Models: Relation Analysis for Compact SMT Encodings

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Abstract

We present Dartagnan, a bounded model checker (BMC) for concurrent programs under weak memory models. Its distinguishing feature is that the memory model is not implemented inside the tool but taken as part of the input. Dartagnan reads CAT, the standard language for memory models, which allows to define x86/TSO, ARMv7, ARMv8, Power, C/C++, and Linux kernel concurrency primitives. BMC with memory models as inputs is challenging. One has to encode into SMT not only the program but also its semantics as defined by the memory model. What makes Dartagnan scale is its relation analysis, a novel static analysis that significantly reduces the size of the encoding. Dartagnan matches or even exceeds the performance of the model-specific verification tools Nidhugg and CBMC, as well as the performance of Herd, a CAT-compatible litmus testing tool. Compared to the unoptimized encoding, the speed-up is often more than two orders of magnitude.

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Gavrilenko, N., Ponce-de-León, H., Furbach, F., Heljanko, K., & Meyer, R. (2019). BMC for Weak Memory Models: Relation Analysis for Compact SMT Encodings. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11561 LNCS, pp. 355–365). Springer Verlag. https://doi.org/10.1007/978-3-030-25540-4_19

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