{"title":"A Counterexample Analysis Method for Assume-Guarantee Verification of Component-Based Software","authors":"Hoang-Viet Tran, Pham Ngoc Hung","doi":"10.1109/KSE53942.2021.9648741","DOIUrl":null,"url":null,"abstract":"This paper presents a method for counterexamples analysis during the assume-guarantee verification process of component-based software. The method helps the process use up all possibilities to reach a conclusive result when verifying large scale software. For this purpose, we improve the equivalence queries answering algorithm on Teacher side to return all possible counterexamples when processing an assumption candidate. The returned counterexamples are analyzed on Learner side to find all possible observation tables which correspond to better assumption candidates for later learning iterations. These observation tables are stored in a list which contains all possibilities for the verification process to reach a conclusive result. Discussions about the importance, correctness, and complexity of the proposed method are included.","PeriodicalId":130986,"journal":{"name":"2021 13th International Conference on Knowledge and Systems Engineering (KSE)","volume":"22 4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 13th International Conference on Knowledge and Systems Engineering (KSE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/KSE53942.2021.9648741","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This paper presents a method for counterexamples analysis during the assume-guarantee verification process of component-based software. The method helps the process use up all possibilities to reach a conclusive result when verifying large scale software. For this purpose, we improve the equivalence queries answering algorithm on Teacher side to return all possible counterexamples when processing an assumption candidate. The returned counterexamples are analyzed on Learner side to find all possible observation tables which correspond to better assumption candidates for later learning iterations. These observation tables are stored in a list which contains all possibilities for the verification process to reach a conclusive result. Discussions about the importance, correctness, and complexity of the proposed method are included.