Department Of Computer Science And Technology

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Author: search.filters.author.Singh, SatwinderSubject: search.filters.subject.Defects

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    Comparative performance of fault-prone prediction classes with k-means clustering and MLP
    (Association for Computing Machinery, 2016) Singh, Satwinder; Singla, Rozy
    Software defect in today's era is most important in the field of software engineering. Most of the organizations used various techniques to predict defects in their products before they are delivered. Defect prediction techniques help the organizations 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. For example clustering, neural networks, support vector machine (SVM) etc. In this paper two defect prediction techniques:-K-means Clustering and Multilayer 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. ? 2016 ACM.
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    Classification of defective modules using object-oriented metrics
    (Inderscience Enterprises Ltd., 2017) Singh, Satwinder; Singla, Rozy
    Software 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.