Arvinder Kaur

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Demand for quality software has undergone rapid growth during the last few years. This is leading to increase in development of machine learning techniques for exploring datasets which can be used in constructing models for predicting quality attributes such as Decision Tree (DT), Support Vector Machine (SVM) and Artificial Neural Network (ANN). This paper(More)
Empirical validation of software metrics used to predict software quality attributes is important to ensure their practical relevance in software organizations. The aim of this work is to find the relation of object-oriented (OO) metrics with fault proneness at different severity levels of faults. For this purpose, different prediction models have been(More)
Importance of software quality is increasing leading to development of new sophisticated techniques, which can be used in constructing models for predicting quality attributes. One such technique is Artificial Neural Network (ANN). This paper examined the application of ANN for software quality prediction using ObjectOriented (OO) metrics. Quality(More)
Empirical validation of software metrics to predict quality using machine learning methods is important to ensure their practical relevance in the software organizations. In this paper, we build a Support Vector Machine (SVM) model to find the relationship between object-oriented metrics given by Chidamber and Kemerer and fault proneness. The proposed model(More)
The importance of software measurement is increasing leading to development of new measurement techniques. As the development of object-oriented software is rising, more and more metrics are being defined for object-oriented languages. Many metrics have been proposed related to various object-oriented constructs like class, coupling, cohesion, inheritance,(More)
Regression testing is primarily a maintenance activity that is performed frequently to ensure the validity of the modified software. In such cases, due to time and cost constraints, the entire test suite cannot be run. Thus, it becomes essential to prioritize the tests in order to cover maximum faults in minimum time. In this paper, ant colony optimization(More)
In this paper an attempt has been made to explore the possibility of the usage of artificial neural networks as Test Oracle. The triangle classification problem has been used as a case study. Results for the usage of unsupervised artificial networks indicate that they are not suitable for this purpose. The Feed-forward back propagation neural networks are(More)