Code review analysis of software system using machine learning techniques

Abstract

Code review is systematic examination of a software system's source code. It is intended to find mistakes overlooked in the initial development phase, improving the overall quality of software and reducing the risk of bugs among other benefits. Reviews are done in various forms such as pair programming, informal walk-through, and formal inspections. Code review has been found to accelerate and streamline the process of software development like very few other practices in software development can. In this paper we propose a machine learning approach for the code reviews in a software system. This would help in faster and a cleaner reviews of the checked in code. The proposed approach is evaluated for feasibility on an open source system eclipse. [1], [2], [3]