用于单元测试的基于搜索的缩减模型

IF 0.2 Q4 ENGINEERING, MULTIDISCIPLINARY
Perla Beatriz Fernández-Oliva, Alejandro Miguel Güemes-Esperón, Martha Dunia Delgado-Dapena, A. Rosete
{"title":"用于单元测试的基于搜索的缩减模型","authors":"Perla Beatriz Fernández-Oliva, Alejandro Miguel Güemes-Esperón, Martha Dunia Delgado-Dapena, A. Rosete","doi":"10.17533/udea.redin.20221098","DOIUrl":null,"url":null,"abstract":"Software tests are fundamental in the reliability and quality of systems, contributing to their positioning in the market. Generating test data is a critical task, as exhaustive testing is costly in time and effort. An adequate design of the test cases, which contemplates a selection of adequate values, can detect a high number of defects. The effectiveness of the test cases is measured according to the number of errors they managed to detect. However, the proposals that address these issues with the use of heuristic algorithms focus on the reduction of generation time and different coverage criteria.\nThis article presents a search-based optimization model for the generation of unit test suites that integrates different test case design techniques considering the significance of the values generated in the detection of errors. The significance of the paths is also taken into account, with the aim of obtaining test cases with greater potential to detect errors. The optimization model uses heuristic algorithms that maximize the coverage of the paths. The results of the experimentation are presented, which show that the proposal presented generates test suits with a high capacity to detect errors. For this, the effectiveness of the generated test suits to detect errors in the mutated code was evaluated.","PeriodicalId":42846,"journal":{"name":"Revista Facultad de Ingenieria, Universidad Pedagogica y Tecnologica de Colombia","volume":null,"pages":null},"PeriodicalIF":0.2000,"publicationDate":"2022-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Search-based reduction model for unit testing\",\"authors\":\"Perla Beatriz Fernández-Oliva, Alejandro Miguel Güemes-Esperón, Martha Dunia Delgado-Dapena, A. Rosete\",\"doi\":\"10.17533/udea.redin.20221098\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Software tests are fundamental in the reliability and quality of systems, contributing to their positioning in the market. Generating test data is a critical task, as exhaustive testing is costly in time and effort. An adequate design of the test cases, which contemplates a selection of adequate values, can detect a high number of defects. The effectiveness of the test cases is measured according to the number of errors they managed to detect. However, the proposals that address these issues with the use of heuristic algorithms focus on the reduction of generation time and different coverage criteria.\\nThis article presents a search-based optimization model for the generation of unit test suites that integrates different test case design techniques considering the significance of the values generated in the detection of errors. The significance of the paths is also taken into account, with the aim of obtaining test cases with greater potential to detect errors. The optimization model uses heuristic algorithms that maximize the coverage of the paths. The results of the experimentation are presented, which show that the proposal presented generates test suits with a high capacity to detect errors. For this, the effectiveness of the generated test suits to detect errors in the mutated code was evaluated.\",\"PeriodicalId\":42846,\"journal\":{\"name\":\"Revista Facultad de Ingenieria, Universidad Pedagogica y Tecnologica de Colombia\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.2000,\"publicationDate\":\"2022-10-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Revista Facultad de Ingenieria, Universidad Pedagogica y Tecnologica de Colombia\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.17533/udea.redin.20221098\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"ENGINEERING, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Revista Facultad de Ingenieria, Universidad Pedagogica y Tecnologica de Colombia","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.17533/udea.redin.20221098","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENGINEERING, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0

摘要

软件测试是系统可靠性和质量的基础,有助于它们在市场上的定位。生成测试数据是一项关键任务,因为详尽的测试在时间和精力上都是昂贵的。测试用例的适当设计,考虑到适当值的选择,可以检测到大量的缺陷。测试用例的有效性是根据它们设法检测到的错误的数量来衡量的。然而,使用启发式算法解决这些问题的建议侧重于减少生成时间和不同的覆盖标准。本文提出了一个基于搜索的优化模型,用于单元测试套件的生成,该模型集成了不同的测试用例设计技术,考虑到在错误检测中生成的值的重要性。路径的重要性也被考虑在内,目的是获得更有可能检测错误的测试用例。优化模型使用启发式算法使路径的覆盖范围最大化。实验结果表明,该方法产生的测试服具有较高的误差检测能力。为此,评估了生成的测试套件在检测突变代码中的错误方面的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Search-based reduction model for unit testing
Software tests are fundamental in the reliability and quality of systems, contributing to their positioning in the market. Generating test data is a critical task, as exhaustive testing is costly in time and effort. An adequate design of the test cases, which contemplates a selection of adequate values, can detect a high number of defects. The effectiveness of the test cases is measured according to the number of errors they managed to detect. However, the proposals that address these issues with the use of heuristic algorithms focus on the reduction of generation time and different coverage criteria. This article presents a search-based optimization model for the generation of unit test suites that integrates different test case design techniques considering the significance of the values generated in the detection of errors. The significance of the paths is also taken into account, with the aim of obtaining test cases with greater potential to detect errors. The optimization model uses heuristic algorithms that maximize the coverage of the paths. The results of the experimentation are presented, which show that the proposal presented generates test suits with a high capacity to detect errors. For this, the effectiveness of the generated test suits to detect errors in the mutated code was evaluated.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
审稿时长
8 weeks
×
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:481959085
Book学术官方微信