Mining usage expertise from version archives

ABSTRACT

In software development, there is an increasing need to find and connect developers with relevant expertise. Existing expertise recommendation systems are mostly based on variations of the Line 10 Rule: developers who changed a file most often have the most implementation expertise. In this paper, we introduce the concept of usage expertise, which manifests itself whenever developers are using functionality, e.g., by calling API methods. We present preliminary results for the ECLIPSE project that demonstrate that our technique allows to recommend experts for files with no or little history, identify developers with similar expertise, and measure the usage of API methods.

REFERENCES

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INDEX TERMS

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

Additional Classification:
  H. Information Systems
  H.2 DATABASE MANAGEMENT
      H.2.8 Database applications
          Subjects: Data mining

  K. Computing Milieux
  K.6 MANAGEMENT OF COMPUTING AND INFORMATION SYSTEMS
      K.6.1 Project and People Management
          Subjects: Staffing

General Terms:
Human Factors, Management

Keywords:
computer-supported cooperative work, expertise recommendation, software repository