{"title":"Wordgen:一个定时单词生成工具","authors":"Benoît Barbot, Nicolas Basset, Alexandre Donzé","doi":"10.1145/3575870.3587116","DOIUrl":null,"url":null,"abstract":"Sampling timed words out of a timed language described as a timed automaton may seem a simple task: start from the initial state, choose a transition and a delay and repeat until an accepting state is reached. Unfortunately, simple approach based on local, on-the-fly rules produces timed words from distributions that are biased in some unpredictable ways. For this reason, approaches have been developed to guarantee that the sampling follows a more desirable distribution defined over the timed language and not over the automaton. One such distribution is the maximal entropy distribution, whose implementation requires several non-trivial computational steps. In this paper, we present Wordgen which combines those different necessary steps into a lightweight standalone tool. The resulting timed words can be mapped to signals used for model-based testing and falsification of cyber-physical systems thanks to a simple interface with the Breach tool.","PeriodicalId":426801,"journal":{"name":"Proceedings of the 26th ACM International Conference on Hybrid Systems: Computation and Control","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Wordgen : a Timed word Generation Tool\",\"authors\":\"Benoît Barbot, Nicolas Basset, Alexandre Donzé\",\"doi\":\"10.1145/3575870.3587116\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Sampling timed words out of a timed language described as a timed automaton may seem a simple task: start from the initial state, choose a transition and a delay and repeat until an accepting state is reached. Unfortunately, simple approach based on local, on-the-fly rules produces timed words from distributions that are biased in some unpredictable ways. For this reason, approaches have been developed to guarantee that the sampling follows a more desirable distribution defined over the timed language and not over the automaton. One such distribution is the maximal entropy distribution, whose implementation requires several non-trivial computational steps. In this paper, we present Wordgen which combines those different necessary steps into a lightweight standalone tool. The resulting timed words can be mapped to signals used for model-based testing and falsification of cyber-physical systems thanks to a simple interface with the Breach tool.\",\"PeriodicalId\":426801,\"journal\":{\"name\":\"Proceedings of the 26th ACM International Conference on Hybrid Systems: Computation and Control\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-05-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 26th ACM International Conference on Hybrid Systems: Computation and Control\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3575870.3587116\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 26th ACM International Conference on Hybrid Systems: Computation and Control","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3575870.3587116","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Sampling timed words out of a timed language described as a timed automaton may seem a simple task: start from the initial state, choose a transition and a delay and repeat until an accepting state is reached. Unfortunately, simple approach based on local, on-the-fly rules produces timed words from distributions that are biased in some unpredictable ways. For this reason, approaches have been developed to guarantee that the sampling follows a more desirable distribution defined over the timed language and not over the automaton. One such distribution is the maximal entropy distribution, whose implementation requires several non-trivial computational steps. In this paper, we present Wordgen which combines those different necessary steps into a lightweight standalone tool. The resulting timed words can be mapped to signals used for model-based testing and falsification of cyber-physical systems thanks to a simple interface with the Breach tool.