Optimized Test Case Generation for Object Oriented Systems Using Weka Open Source Software

Rajvir Singh, Anita Singhrova, R. Bhatia
{"title":"Optimized Test Case Generation for Object Oriented Systems Using Weka Open Source Software","authors":"Rajvir Singh, Anita Singhrova, R. Bhatia","doi":"10.4018/IJOSSP.2018070102","DOIUrl":null,"url":null,"abstract":"Detection of fault proneness classes helps software testers to generate effective class level test cases. In this article, a novel technique is presented for an optimized test case generation for ant-1.7 open source software. Class level object oriented (OO) metrics are considered as effective means to find fault proneness classes. The open source software ant-1.7 is considered for the evaluation of proposed techniques as a case study. The proposed mathematical model is the first of its kind generated using Weka open source software to select effective OO metrics. Effective and ineffective OO metrics are identified using feature selection techniques for generating test cases to cover fault proneness classes. In this methodology, only effective metrics are considered for assigning weights to test paths. The results indicate that the proposed methodology is effective and efficient as the average fault exposition potential of generated test cases is 90.16% and test cases execution time saving is 45.11%.","PeriodicalId":53605,"journal":{"name":"International Journal of Open Source Software and Processes","volume":"73 1","pages":"15-35"},"PeriodicalIF":0.0000,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Open Source Software and Processes","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4018/IJOSSP.2018070102","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Computer Science","Score":null,"Total":0}
引用次数: 3

Abstract

Detection of fault proneness classes helps software testers to generate effective class level test cases. In this article, a novel technique is presented for an optimized test case generation for ant-1.7 open source software. Class level object oriented (OO) metrics are considered as effective means to find fault proneness classes. The open source software ant-1.7 is considered for the evaluation of proposed techniques as a case study. The proposed mathematical model is the first of its kind generated using Weka open source software to select effective OO metrics. Effective and ineffective OO metrics are identified using feature selection techniques for generating test cases to cover fault proneness classes. In this methodology, only effective metrics are considered for assigning weights to test paths. The results indicate that the proposed methodology is effective and efficient as the average fault exposition potential of generated test cases is 90.16% and test cases execution time saving is 45.11%.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
使用Weka开源软件优化面向对象系统的测试用例生成
对易出错类的检测有助于软件测试人员生成有效的类级测试用例。在本文中,提出了一种新的技术,用于为ant-1.7开源软件生成优化的测试用例。类级面向对象度量被认为是发现易出错类的有效手段。将开源软件ant-1.7作为一个案例研究来评估所提出的技术。所提出的数学模型是第一个使用Weka开源软件生成的用于选择有效OO指标的数学模型。有效和无效的OO度量是使用特征选择技术来识别的,这些技术用于生成测试用例,以覆盖容易出错的类。在这个方法中,只有有效的度量被认为是分配权重给测试路径。结果表明,该方法是有效的,生成的测试用例的平均故障揭示率为90.16%,测试用例执行时间节省45.11%。
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 去求助
来源期刊
CiteScore
1.90
自引率
0.00%
发文量
16
期刊介绍: The International Journal of Open Source Software and Processes (IJOSSP) publishes high-quality peer-reviewed and original research articles on the large field of open source software and processes. This wide area entails many intriguing question and facets, including the special development process performed by a large number of geographically dispersed programmers, community issues like coordination and communication, motivations of the participants, and also economic and legal issues. Beyond this topic, open source software is an example of a highly distributed innovation process led by the users. Therefore, many aspects have relevance beyond the realm of software and its development. In this tradition, IJOSSP also publishes papers on these topics. IJOSSP is a multi-disciplinary outlet, and welcomes submissions from all relevant fields of research and applying a multitude of research approaches.
期刊最新文献
Organizational Influencers in Open-Source Software Projects Enhancing Clustering Performance Using Topic Modeling-Based Dimensionality Reduction Cross Project Software Refactoring Prediction Using Optimized Deep Learning Neural Network with the Aid of Attribute Selection Bug Triage Automation Approaches Modelling and Simulation of Patient Flow in the Emergency Department During the COVID-19 Pandemic Using Hierarchical Coloured Petri Net
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1