{"title":"Evaluation of Software Testing Adequacy based on AHP and BPNN","authors":"Wenhong Liu, Jinliang Gao, Qiong Xue, Dong Guo, Wei Zhang","doi":"10.1109/QRS-C57518.2022.00031","DOIUrl":null,"url":null,"abstract":"There are many factors that affect the evaluation of software testing adequacy, and it is easy to be influenced by human factors when using conventional evaluation methods. Analytic hierarchy process (AHP) is a kind of simple and flexible and practical multi-criteria decision-making method, which is especially suitable for those problems that are difficult to be completely quantitatively analyzed. BP neural network (BPNN) is a widely used intelligent algorithm based on biological neural network, which can better simulate experts for evaluation. Therefore, AHP and BPNN can be combined to evaluate software testing adequacy. Firstly, the evaluation index system of software testing adequacy is constructed from two aspects of testing agency and testing project, and then the comprehensive evaluation model of software testing adequacy is given by using AHP and BPNN. Finally, an example is analyzed.","PeriodicalId":183728,"journal":{"name":"2022 IEEE 22nd International Conference on Software Quality, Reliability, and Security Companion (QRS-C)","volume":"106 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE 22nd International Conference on Software Quality, Reliability, and Security Companion (QRS-C)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/QRS-C57518.2022.00031","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
There are many factors that affect the evaluation of software testing adequacy, and it is easy to be influenced by human factors when using conventional evaluation methods. Analytic hierarchy process (AHP) is a kind of simple and flexible and practical multi-criteria decision-making method, which is especially suitable for those problems that are difficult to be completely quantitatively analyzed. BP neural network (BPNN) is a widely used intelligent algorithm based on biological neural network, which can better simulate experts for evaluation. Therefore, AHP and BPNN can be combined to evaluate software testing adequacy. Firstly, the evaluation index system of software testing adequacy is constructed from two aspects of testing agency and testing project, and then the comprehensive evaluation model of software testing adequacy is given by using AHP and BPNN. Finally, an example is analyzed.