An open framework for CVS repository querying, analysis and visualization

ABSTRACT

We present an open framework for visual mining of CVS software repositories. We address three aspects: data extraction, analysis and visualization. We first discuss the challenges of CVS data extraction and storage, and propose a flexible way to deal with CVS implementation inconsistencies. We next present a new technique to enrich the raw data with information about artifacts showing similar evolution. Finally, we propose a visualization backend and show its applicability on industry-size repositories.

REFERENCES

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INDEX TERMS

Primary Classification:
  D. Software
  D.2 SOFTWARE ENGINEERING
      D.2.7 Distribution, Maintenance, and Enhancement
          Subjects: Documentation

Additional Classification:
  D. Software
  D.2 SOFTWARE ENGINEERING
      D.2.7 Distribution, Maintenance, and Enhancement
          Subjects: Restructuring, reverse engineering, and reengineering

  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.3 Information Search and Retrieval
          Subjects: Clustering; Query formulation

  I. Computing Methodologies
  I.3 COMPUTER GRAPHICS
      I.3.8 Applications

General Terms:
Documentation, Management, Measurement

Keywords:
CVS repositories, evolution visualization, software visualization