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Software testing which is carried out for the elimination of the software defects is one of the significant activities to achieve software quality. However, testing each fragment of the software is impossible and defects still occur even after several detailed test activities. Therefore, there is a need for effective methods to detect bugs in software. It is possible to detect faulty portions of the code earlier by examining the characteristics of the code. Serving this purpose, bug prediction activities help to detect the presence of defects as early as possible in an automated fashion. As a part of the ongoing thesis study, an effective model is aimed to be developed in order to predict software entities having bugs. A public bug database and ATM monitoring software source code are used for the creation of the model and to find the performance of the study.

Bug Prediction for an ATM Monitoring Software - Use of Logistic Regression Analysis for Bug Prediction