{"title":"利用反向归纳法从基于比率的时间测试序列重构时间符号轨迹","authors":"Junaid Iqbal, D. Truscan, J. Vain, Ivan Porres","doi":"10.1145/3123779.3123813","DOIUrl":null,"url":null,"abstract":"As of today, model-based testing is considered as a leading-edge technology in the IT industry. In model-based testing, an implementation under test is tested for compliance with a model that describes the required behaviour of the implementation. Uppaal Tron is a popular tool for online model-based conformance testing of real-time systems; it uses the Uppaal verification engine to generate and convert on-the-fly timed symbolic traces into concrete test sequences. Among the advantages of online testing is the reduction of the symbolic state space needed for computing traces, better addressing non-determinism, as well as the possibility to execute longer-lasting test runs. However, analysing and debugging long test runs can be tedious and time-consuming especially when analysing root causes of failed tests. In game theory, backward-induction is a process to reason backwards in time, from the end of a problem or situation, in order to determine a sequence of optimal actions. In this paper, we propose an approach to reconstruct symbolic traces from test sequences generated by Uppaal Tron using backward-induction. The resulting symbolic traces can be imported in the Uppaal tool and visualised in the Uppaal simulator. The evaluation of the implementation of the approach shows that it has the potential to satisfy the needs of industrial level testing.","PeriodicalId":405980,"journal":{"name":"Proceedings of the Fifth European Conference on the Engineering of Computer-Based Systems","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2017-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Reconstructing timed symbolic traces from rtioco-based timed test sequences using backward-induction\",\"authors\":\"Junaid Iqbal, D. Truscan, J. Vain, Ivan Porres\",\"doi\":\"10.1145/3123779.3123813\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"As of today, model-based testing is considered as a leading-edge technology in the IT industry. In model-based testing, an implementation under test is tested for compliance with a model that describes the required behaviour of the implementation. Uppaal Tron is a popular tool for online model-based conformance testing of real-time systems; it uses the Uppaal verification engine to generate and convert on-the-fly timed symbolic traces into concrete test sequences. Among the advantages of online testing is the reduction of the symbolic state space needed for computing traces, better addressing non-determinism, as well as the possibility to execute longer-lasting test runs. However, analysing and debugging long test runs can be tedious and time-consuming especially when analysing root causes of failed tests. In game theory, backward-induction is a process to reason backwards in time, from the end of a problem or situation, in order to determine a sequence of optimal actions. In this paper, we propose an approach to reconstruct symbolic traces from test sequences generated by Uppaal Tron using backward-induction. The resulting symbolic traces can be imported in the Uppaal tool and visualised in the Uppaal simulator. The evaluation of the implementation of the approach shows that it has the potential to satisfy the needs of industrial level testing.\",\"PeriodicalId\":405980,\"journal\":{\"name\":\"Proceedings of the Fifth European Conference on the Engineering of Computer-Based Systems\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-08-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the Fifth European Conference on the Engineering of Computer-Based Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3123779.3123813\",\"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 Fifth European Conference on the Engineering of Computer-Based Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3123779.3123813","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Reconstructing timed symbolic traces from rtioco-based timed test sequences using backward-induction
As of today, model-based testing is considered as a leading-edge technology in the IT industry. In model-based testing, an implementation under test is tested for compliance with a model that describes the required behaviour of the implementation. Uppaal Tron is a popular tool for online model-based conformance testing of real-time systems; it uses the Uppaal verification engine to generate and convert on-the-fly timed symbolic traces into concrete test sequences. Among the advantages of online testing is the reduction of the symbolic state space needed for computing traces, better addressing non-determinism, as well as the possibility to execute longer-lasting test runs. However, analysing and debugging long test runs can be tedious and time-consuming especially when analysing root causes of failed tests. In game theory, backward-induction is a process to reason backwards in time, from the end of a problem or situation, in order to determine a sequence of optimal actions. In this paper, we propose an approach to reconstruct symbolic traces from test sequences generated by Uppaal Tron using backward-induction. The resulting symbolic traces can be imported in the Uppaal tool and visualised in the Uppaal simulator. The evaluation of the implementation of the approach shows that it has the potential to satisfy the needs of industrial level testing.