{"title":"Geração Automática de Dados e Tratamento de Não Executabilidade no Teste Estrutural de Software","authors":"P. Bueno, Mario Jino","doi":"10.5753/sbes.1999.23929","DOIUrl":null,"url":null,"abstract":"A tool and techniques are presented for test data generation and infeasibility identification in structural software testing technique. The tool is based on: the Dynamic Technique; search using Genetic Algorithms; and reuse of solutions through Case-Based Reasoning. The objective is to automatically generate input data which execute complete paths in a program and identify path infeasibility when this is the case; this is done through the Potential Infeasibility Dynamic Identification Heuristic proposed. An experiment shows the validity of the developed solutions and the benefit of using the tool. Results attained indicate that, despite the general undecidability of the problems, partial solutions can be useful for software testing practice.","PeriodicalId":325756,"journal":{"name":"Anais do XIII Simpósio Brasileiro de Engenharia de Software (SBES 1999)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1999-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Anais do XIII Simpósio Brasileiro de Engenharia de Software (SBES 1999)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5753/sbes.1999.23929","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
A tool and techniques are presented for test data generation and infeasibility identification in structural software testing technique. The tool is based on: the Dynamic Technique; search using Genetic Algorithms; and reuse of solutions through Case-Based Reasoning. The objective is to automatically generate input data which execute complete paths in a program and identify path infeasibility when this is the case; this is done through the Potential Infeasibility Dynamic Identification Heuristic proposed. An experiment shows the validity of the developed solutions and the benefit of using the tool. Results attained indicate that, despite the general undecidability of the problems, partial solutions can be useful for software testing practice.