Software Defect Prediction Using Genetic Programming and Neural Networks

Thisarticledescribeshowclassificationmethodsonsoftwaredefectpredictioniswidelyresearched duetotheneedtoincreasethesoftwarequalityanddecreasetestingefforts.However,findingsofpast researchesdoneonthisissuehasnotshownanyclassifierwhichprovestobesuperiortotheother. Additionally,thereisalackofresearchthatstudiestheeffectsandaccuracyofgeneticprogramming on softwaredefectprediction.To find solutions for thisproblem, a comparative softwaredefect predictionexperimentbetweengeneticprogrammingandneuralnetworksareperformedonfour datasetsfromtheNASAMetricsDatarepository.Generally,aninterestingdegreeofaccuracyis detected,whichshowshowthemetric-basedclassificationisuseful.Nevertheless,thisarticlespecifies thattheapplicationandusageofgeneticprogrammingishighlyrecommendedduetothedetailed analysisitprovides,aswellasanimportantfeatureinthisclassificationmethodwhichallowsthe viewingofeachattributesimpactinthedataset. KeywORDS Classification, Genetic Algorithm, Genetic Programming, Machine learning, Nasa Metrics, Neural Networks, Software Defect Prediction, Testing

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