Mutation Testing for Rule-Based Verification of Railway Signaling Data

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@Article{Laibinis:2021:R,

• author = "Linas Laibinis and Alexei Iliasov and Alexander Romanovsky",
• title = "Mutation Testing for Rule-Based Verification of Railway Signaling Data",
• journal = "IEEE Transactions on Reliability",
• year = "2021",
• volume = "70",
• number = "2",
• pages = "676--691",
• abstract = "Industry applications of formal verification to signaling control tables require formulation of a large number of mathematical conjectures expressing verification rules. It is paramount to establish the validity and completeness of these conjectures. This article discusses a mutation-based validation technique that guides domain experts in the construction of such verification rules. Furthermore, we use genetic programming to quickly generate millions of well-formed data mutations of control tables and to synthesize mutation programs. The technique is illustrated by a synthetic running example and a discussion of our experience in using it in the industrial setting.",
• keywords = "genetic algorithms, genetic programming",
• DOI = "doi:10.1109/TR.2020.3047462",
• ISSN = "1558-1721",
• month = jun,
• notes = "Also known as \cite{9324982}",

}

Genetic Programming entries for Linas Laibinis Alexei Iliasov Alexander Romanovsky

Citations