An Exploratory Analysis for Studying Software Evolution: Time-Delayed Correlation Analysis

We propose an exploratory analysis method for software repositories so that you can study software evolution without an explicit goal. The method extends the traditional correlation analysis to consider a time lag between any pair of metrics. Using data collected from three kinds of repositories, the method automatically calculates optimal parameters to deal with a time lag between metrics and returns the highest correlation coefficient for each pair of metrics. Our case study using one hundred metrics data from three OSS projects shows that the method allows us to find unexpected relationships in some pairs of metrics if we only use the traditional correlation analysis and that using such relationships can be used to build an analysis goal to understand software evolution.

I. Introduction

Software evolution [1], [2] refers to changes to software products and process over time in order to adapt users' various needs to circumstances of the moment. Since software systems are essential for our daily life, they must be maintained for a long time in adapting to environmental changes, adding necessary functions at the time and keeping the quality of the software systems [3]. It is also necessary to understand the impact of software evolution on software quality and user satisfaction. In the modern, large-scale software development, it is hard to correctly understand the impact of software evolution on software quality and user satisfaction.