Analytical Approach to Cross Project Defect Prediction

Abstract

Ensuring software quality has been an issue since the very beginning of software industry. Now with the advancement in technology, tools and development cycles, new paradigms have emerged to tackle the challenges of software quality management. Software defect prediction (SDP) is one of those to help recognize the code blocks, classes, methods or files which contain the most bugs. It helps the programmer to prioritize those classes or methods for testing and bug fixing. It gives maximum coverage and hence reduces the cost of testing, bug fixing and saves time. This paper provides a way to discover challenges encountered during the SDP. We provide a comprehensive study of different defect prediction techniques, tools, datasets, algorithms, modelling tools and application areas of cross-project defect prediction, granularity levels used and SDP challenges.