MbSRT2: Model-Based Selective Regression Testing with Traceability

L. Naslavsky, H. Ziv, D. Richardson
{"title":"MbSRT2: Model-Based Selective Regression Testing with Traceability","authors":"L. Naslavsky, H. Ziv, D. Richardson","doi":"10.1109/ICST.2010.61","DOIUrl":null,"url":null,"abstract":"Widespread adoption of model-centric development has created opportunities for software testing, with Model-Based Testing (MBT). MBT supports the generation of test cases from models and the demonstration of model and source-code compliance. Models evolve, much like source code. Thus, an important activity of MBT is selective regression testing, which selects test cases for retest based on model modifications, rather than source-code modifications. This activity explores relationships between model elements and test cases that traverse those elements to locate retest able test cases. We contribute an approach and prototype to model-based selective regression testing, whereby fine-grain traceability relationships among entities in models and test cases are persisted into a traceability infrastructure throughout the test generation process: the relationships represent reasons for test case creation and are used to select test cases for re-run. The approach builds upon existing regression test selection techniques and adopts scenarios as behavioral modeling perspective. We analyze precision, efficiency and safety of the approach through case studies and through theoretical and intuitive reasoning.","PeriodicalId":192678,"journal":{"name":"2010 Third International Conference on Software Testing, Verification and Validation","volume":"42 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"21","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 Third International Conference on Software Testing, Verification and Validation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICST.2010.61","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 21

Abstract

Widespread adoption of model-centric development has created opportunities for software testing, with Model-Based Testing (MBT). MBT supports the generation of test cases from models and the demonstration of model and source-code compliance. Models evolve, much like source code. Thus, an important activity of MBT is selective regression testing, which selects test cases for retest based on model modifications, rather than source-code modifications. This activity explores relationships between model elements and test cases that traverse those elements to locate retest able test cases. We contribute an approach and prototype to model-based selective regression testing, whereby fine-grain traceability relationships among entities in models and test cases are persisted into a traceability infrastructure throughout the test generation process: the relationships represent reasons for test case creation and are used to select test cases for re-run. The approach builds upon existing regression test selection techniques and adopts scenarios as behavioral modeling perspective. We analyze precision, efficiency and safety of the approach through case studies and through theoretical and intuitive reasoning.
MbSRT2:具有追溯性的基于模型的选择性回归测试
以模型为中心的开发的广泛采用为基于模型的测试(MBT)的软件测试创造了机会。MBT支持从模型中生成测试用例,以及模型和源代码遵从性的演示。模型不断发展,就像源代码一样。因此,MBT的一个重要活动是选择性回归测试,它根据模型修改而不是源代码修改来选择测试用例进行重新测试。这个活动探索模型元素和测试用例之间的关系,遍历那些元素来定位可重新测试的测试用例。我们为基于模型的选择性回归测试提供了一种方法和原型,据此,模型和测试用例中实体之间的细粒度跟踪关系在整个测试生成过程中被持久化到一个跟踪基础结构中:这些关系表示测试用例创建的原因,并用于选择重新运行的测试用例。该方法建立在现有的回归测试选择技术之上,并采用场景作为行为建模视角。我们通过案例研究以及理论和直觉推理来分析该方法的准确性、效率和安全性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
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