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基于遗传算法的结构测试数据自动生成.docx

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基于遗传算法的结构测试数据自动生成 Introduction: Testingisanintegralpartofthesoftwaredevelopmentprocess.Itisusedtoverifywhetherthesoftwaremeetsitsfunctionalandnon-functionalrequirements.Structuraltestingisatypeoftestingthatinvolvesexaminingtheinternalsofthecode.Itisusedtocheckwhetherthecodestructureiscorrect,whetheranycodingerrorsexist,andwhetherthecodecanhandleextremetestingconditions. Testdataisnecessaryforstructuraltesting.Itinvolvescreatingasetofinputvaluesandexpectedoutputvaluestoexerciseaspecificsoftwarefeature.Thetestdatashouldbecomprehensive,i.e.,itshouldcoverallpossibleprogramexecutionpaths.Thegenerationoftherighttestdataisatime-consumingtask,andoften,developersmakemistakesthatcouldleadtoincorrectorinsufficienttesting.Toavoidsuchmishaps,thispaperproposesanapproachtogeneratetestdatausinggeneticalgorithms. Overview: Geneticalgorithmsarepartofcomputationalintelligenceandareusedforsolvingoptimizationproblems.Theymimicthenaturalprocessofevolutionandsurvivalofthefittest.Byapplyinggeneticalgorithmstoproblem-solving,wecanfindsolutionstooptimizethegivenproblem.Thispaperproposesusinggeneticalgorithmstooptimizethetestdatagenerated. Methodology: Theproposedmethodologyinvolvesthefollowingsteps: 1.Chromosomerepresentation–Thefirststepistorepresentthetestdatainaformatthatthegeneticalgorithmcanuse.Thechromosomeisthebasicunitofthegeneticalgorithm.Inthisstep,werepresentthetestdatainachromosome.Thechromosomeinthiscaseisasetofinputvalues,whichrepresentthetestcases. 2.Initialpopulation-Thesecondstepinvolvescreatinganinitialpopulationoftestcases.Testcasesarecreatedrandomly,andthenumberoftestcasesisdeterminedbythesizeofthepopulation. 3.Fitnessfunction–Thethirdstepistoconstructthefitnessfunction.Geneticalgorithmssolveproblemsbyrepeatedlyevaluatingandevolvingthepopulationofchromosomes.Inthiscase,fitnessreferstohowwellachromosomemeetsthetestcriteria.Thefitnessfunctionevaluateseachchromosomebasedonthefollowingcriteria:Codecoverage,Pathcoverage,andBranchcoverage. 4.Selection-Thefourthstepinvolvesselec