Marek Chalupa, Thomas A. Henzinger, Nicolas Mazzocchi, N. Ege Saraç
{"title":"QuAK:定量自动机工具包","authors":"Marek Chalupa, Thomas A. Henzinger, Nicolas Mazzocchi, N. Ege Saraç","doi":"arxiv-2409.03569","DOIUrl":null,"url":null,"abstract":"System behaviors are traditionally evaluated through binary classifications\nof correctness, which do not suffice for properties involving quantitative\naspects of systems and executions. Quantitative automata offer a more nuanced\napproach, mapping each execution to a real number by incorporating weighted\ntransitions and value functions generalizing acceptance conditions. In this\npaper, we introduce QuAK, the first tool designed to automate the analysis of\nquantitative automata. QuAK currently supports a variety of quantitative\nautomaton types, including Inf, Sup, LimInf, LimSup, LimInfAvg, and LimSupAvg\nautomata, and implements decision procedures for problems such as emptiness,\nuniversality, inclusion, equivalence, as well as for checking whether an\nautomaton is safe, live, or constant. Additionally, QuAK is able to compute\nextremal values when possible, construct safety-liveness decompositions, and\nmonitor system behaviors. We demonstrate the effectiveness of QuAK through\nexperiments focusing on the inclusion, constant-function check, and monitoring\nproblems.","PeriodicalId":501124,"journal":{"name":"arXiv - CS - Formal Languages and Automata Theory","volume":"2013 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"QuAK: Quantitative Automata Kit\",\"authors\":\"Marek Chalupa, Thomas A. Henzinger, Nicolas Mazzocchi, N. Ege Saraç\",\"doi\":\"arxiv-2409.03569\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"System behaviors are traditionally evaluated through binary classifications\\nof correctness, which do not suffice for properties involving quantitative\\naspects of systems and executions. Quantitative automata offer a more nuanced\\napproach, mapping each execution to a real number by incorporating weighted\\ntransitions and value functions generalizing acceptance conditions. In this\\npaper, we introduce QuAK, the first tool designed to automate the analysis of\\nquantitative automata. QuAK currently supports a variety of quantitative\\nautomaton types, including Inf, Sup, LimInf, LimSup, LimInfAvg, and LimSupAvg\\nautomata, and implements decision procedures for problems such as emptiness,\\nuniversality, inclusion, equivalence, as well as for checking whether an\\nautomaton is safe, live, or constant. Additionally, QuAK is able to compute\\nextremal values when possible, construct safety-liveness decompositions, and\\nmonitor system behaviors. We demonstrate the effectiveness of QuAK through\\nexperiments focusing on the inclusion, constant-function check, and monitoring\\nproblems.\",\"PeriodicalId\":501124,\"journal\":{\"name\":\"arXiv - CS - Formal Languages and Automata Theory\",\"volume\":\"2013 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-09-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"arXiv - CS - Formal Languages and Automata Theory\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/arxiv-2409.03569\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - CS - Formal Languages and Automata Theory","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2409.03569","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
System behaviors are traditionally evaluated through binary classifications
of correctness, which do not suffice for properties involving quantitative
aspects of systems and executions. Quantitative automata offer a more nuanced
approach, mapping each execution to a real number by incorporating weighted
transitions and value functions generalizing acceptance conditions. In this
paper, we introduce QuAK, the first tool designed to automate the analysis of
quantitative automata. QuAK currently supports a variety of quantitative
automaton types, including Inf, Sup, LimInf, LimSup, LimInfAvg, and LimSupAvg
automata, and implements decision procedures for problems such as emptiness,
universality, inclusion, equivalence, as well as for checking whether an
automaton is safe, live, or constant. Additionally, QuAK is able to compute
extremal values when possible, construct safety-liveness decompositions, and
monitor system behaviors. We demonstrate the effectiveness of QuAK through
experiments focusing on the inclusion, constant-function check, and monitoring
problems.