Investigating the Effectiveness of Greedy Algorithm on Open Source Software Systems for Determining Refactoring Sequence

The deeper problem in the source code are the bad smells that indicates something is wrong and if they are not detected timely, then they lead towards the complete deterioration of the working software causing major financial and productivity loss. Refactoring helps in removing these bad smells by improving internal quality attributes of the software without affecting its external behaviour. However refactoring needs to be applied in a controlled manner. In this study an approach has been propose for determining an optimal refactoring sequence that will maximize the source-code maintainability using greedy algorithm. The proposed approach selects the most optimum sequence at every step-in hope of finding the global optimum solution. We conduct an empirical analysis on four open-source software and select those classes that have bad smells greater than or equal to four. Further filtration is done by selecting those classes from the group that have high value of source code lines. We demonstrate the effectiveness of our approach using concrete examples of the experimental dataset and presenting summary results.