Combining Single-Version and Evolutionary Dependencies for Software-Change Prediction

Abstract

The paper advocates the need for the investigation and development of a software-change prediction methodology that combines the change sets estimated from software dependency analysis (via single-version analysis) and the actual change sets found in software version histories (via multiple-version analysis). Traditionally prescribed methodologies such as Impact Analysis (IA) are based on the former, whereas a more recent methodology, mining software repository (MSR), is based on the latter. The research hypothesis is that combining these two methodologies will result in an overall improved support for software-change prediction.