Wordgen : a Timed word Generation Tool

Benoît Barbot, Nicolas Basset, Alexandre Donzé
{"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}
引用次数: 1

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.
Wordgen:一个定时单词生成工具
从描述为定时自动机的定时语言中采样定时单词似乎是一项简单的任务:从初始状态开始,选择转换和延迟,然后重复,直到达到可接受状态。不幸的是,基于局部动态规则的简单方法从分布中产生计时词,这些分布以某种不可预测的方式存在偏差。由于这个原因,已经开发了一些方法来保证采样遵循在定时语言上而不是在自动机上定义的更理想的分布。其中一种分布是最大熵分布,其实现需要几个重要的计算步骤。在本文中,我们介绍了Wordgen,它将这些不同的必要步骤组合成一个轻量级的独立工具。由于Breach工具的简单接口,生成的定时词可以映射到用于基于模型的测试和网络物理系统伪造的信号。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信