Classification of defective modules using object-oriented metrics

dc.contributor.authorSingh, Satwinder
dc.contributor.authorSingla, Rozy
dc.date.accessioned2018-07-14T01:18:38Z
dc.date.accessioned2024-08-14T05:05:39Z
dc.date.available2018-07-14T01:18:38Z
dc.date.available2024-08-14T05:05:39Z
dc.date.issued2017
dc.description.abstractSoftware defect in today's era is crucial in the field of software engineering. Most of the organisations use various techniques to predict defects in their products before they are delivered. Defect prediction techniques help the organisations to use their resources effectively which results in lower cost and time requirements. There are various techniques that are used for predicting defects in software before it has to be delivered, e.g., clustering, neural networks, support vector machine (SVM). In this paper two defect prediction techniques: K-means clustering and multi-layer perceptron model (MLP) are compared. Both the techniques are implemented on different platforms. K-means clustering is implemented using WEKA tool and MLP is implemented using SPSS. The results are compared to find which algorithm produces better results. In this paper object-oriented metrics are used for predicting defects in the software. Copyright ? 2017 Inderscience Enterprises Ltd.en_US
dc.identifier.citationSingh, S., & Singla, R. (2017). Classification of defective modules using object-oriented metrics. International Journal of Intelligent Systems Technologies and Applications, 16(1), 1-13. doi: 10.1504/IJISTA.2017.081311en_US
dc.identifier.doi10.1504/IJISTA.2017.081311
dc.identifier.issn17408865
dc.identifier.urihttps://kr.cup.edu.in/handle/32116/1271
dc.language.isoen_USen_US
dc.publisherInderscience Enterprises Ltd.en_US
dc.subjectDefectsen_US
dc.subjectForecastingen_US
dc.subjectNeural networksen_US
dc.subjectSoftware engineeringen_US
dc.subjectSupport vector machinesen_US
dc.subjectDefect predictionen_US
dc.subjectK-means clusteringen_US
dc.subjectMulti layer perceptronen_US
dc.subjectObject oriented metricsen_US
dc.subjectSoftware defectsen_US
dc.subjectTime requirementsen_US
dc.subjectWEKAen_US
dc.subjectWeka toolen_US
dc.subjectObject oriented programmingen_US
dc.titleClassification of defective modules using object-oriented metricsen_US
dc.title.journalInternational Journal of Intelligent Systems Technologies and Applicationsen_US
dc.typeArticleen_US

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