基于数据挖掘的软件缺陷预测测试用例优先级划分框架

Q4 Computer Science

International Journal of Open Source Software and Processes Pub Date : 2017-01-01 DOI:10.4018/IJOSSP.2017010102

E. Alsukhni, A. Saifan, Hanadi Alawneh

引用次数: 2

摘要

Testcasesdonothavethesameimportancewhenusedtodetectfaultsinsoftware;therefore，itis moreefficienttotestthesystemwiththetestcasesthathavetheabilitytodetectthefaults。This researchproposesanewframeworkthatcombinesdataminingtechniquestoprioritizethetestcases。[Itenhancesfaultpredictionanddetectionusingtwodifferenttechniques:1)thedataminingregression classifierthatdependsonsoftwaremetricstopredictdefectivemodules，and2)thek-meansclustering techniquethatisusedtoselectandprioritizetestcasestoidentifythefaultearly。Ourapproachof testcaseprioritizationyieldsgoodresultsincomparisonwithotherstudies。Theauthorsusedthe AveragePercentageofFaultsDetection(APFD)metrictoevaluatetheproposedframework，which resultsin19.9%forallsystemmodulesand25.7%fordefectiveones。Ourresultsgiveusanindication thatitiseffectivetostartthetestingprocesswiththemostdefectivemodulesinsteadoftestingall modulesarbitraryarbitrarily。关键词数据挖掘，软件缺陷预测，软件测试，测试用例优先级

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A New Data Mining-Based Framework to Test Case Prioritization Using Software Defect Prediction

Testcasesdonothavethesameimportancewhenusedtodetectfaultsinsoftware;therefore,itis moreefficienttotestthesystemwiththetestcasesthathavetheabilitytodetectthefaults.This researchproposesanewframeworkthatcombinesdataminingtechniquestoprioritizethetestcases. Itenhancesfaultpredictionanddetectionusingtwodifferenttechniques:1)thedataminingregression classifierthatdependsonsoftwaremetricstopredictdefectivemodules,and2)thek-meansclustering techniquethatisusedtoselectandprioritizetestcasestoidentifythefaultearly.Ourapproachof testcaseprioritizationyieldsgoodresultsincomparisonwithotherstudies.Theauthorsusedthe AveragePercentageofFaultsDetection(APFD)metrictoevaluatetheproposedframework,which resultsin19.9%forallsystemmodulesand25.7%fordefectiveones.Ourresultsgiveusanindication thatitiseffectivetostartthetestingprocesswiththemostdefectivemodulesinsteadoftestingall modulesarbitraryarbitrarily. KeywORDS Data Mining, Software Defect Prediction, Software Testing, Test Case Prioritization

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来源期刊

International Journal of Open Source Software and Processes Computer Science-Software

CiteScore

1.90

自引率

0.00%

发文量

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.