Analyzing software evolution through feature views: Research Articles

  • Authors:

  • Orla Greevy;Stéphane Ducasse;Tudor Gîrba

  • Affiliations:

  • Software Composition Group, Institute for Applied Mathematics and Computer Science, University of Berne, Neubrückstrasse 10, CH-3012 Berne, Switzerland;LISTIC, University of Savoie, France;Software Composition Group, Institute for Applied Mathematics and Computer Science, University of Berne, Neubrückstrasse 10, CH-3012 Berne, Switzerland

  • Venue:
  • Journal of Software Maintenance and Evolution: Research and Practice
  • Year:
  • 2006

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Abstract

Features encapsulate the domain knowledge of a software system and thus are valuable sources of information for a reverse engineer. When analyzing the evolution of a system, we need to know how and which features were modified to recover both the change intention and extent, namely which source artifacts are affected. Typically, the implementation of a feature crosscuts a number of source artifacts. To obtain a mapping between features and the source artifacts, we exercise the features and capture their execution traces. However, this results in large traces that are difficult to interpret. To tackle this issue we compact the traces into simple sets of source artifacts that participate in a feature's runtime behavior. We refer to these compacted traces as feature views. Within a feature view, we partition the source artifacts into disjoint sets of characterized software entities. The characterization defines the level of participation of a source entity in the features. We then analyze the features over several versions of a system and we plot their evolution to reveal how and which features were affected by code changes. We show the usefulness of our approach by applying it to a case study where we address the problem of merging parallel development tracks of the same system. Copyright © 2006 John Wiley & Sons, Ltd.