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

  • Authors:

  • Huzefa Kagdi;Jonathan I. Maletic

  • Affiliations:

  • Kent State University, USA;Kent State University, USA

  • Venue:
  • MSR '07 Proceedings of the Fourth International Workshop on Mining Software Repositories
  • Year:
  • 2007

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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.