Program restructuring using clustering techniques

  • Authors:

  • Chung-Horng Lung;Xia Xu;Marzia Zaman;Anand Srinivasan

  • Affiliations:

  • Department of Systems and Computer Engineering, Carleton University, Ottawa, Ont., Canada;Department of Systems and Computer Engineering, Carleton University, Ottawa, Ont., Canada;Cistel Technology, Ottawa, Ont., Canada;EION Inc., Ottawa, Ont., Canada

  • Venue:
  • Journal of Systems and Software - Special issue: Selected papers from the 4th source code analysis and manipulation (SCAM 2004) workshop
  • Year:
  • 2006

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Abstract

Program restructuring is a key method for improving the quality of ill-structured programs, thereby increasing the understandability and reducing the maintenance cost. It is a challenging task and a great deal of research is still ongoing. This paper presents an approach to program restructuring inside of a function based on clustering techniques with cohesion as the major concern. Clustering has been widely used to group related entities together. The approach focuses on automated support for identifying ill-structured or low-cohesive functions and providing heuristic advice in both the development and evolution phases. A new similarity measure is defined and studied intensively specifically from the function perspective. A comparative study on three different hierarchical agglomerative clustering algorithms is also conducted. The best algorithm is applied to restructuring of functions of a real industrial system. The empirical observations show that the heuristic advice provided by the approach can help software designers make better decision of why and how to restructure a program. Specific source code level software metrics are presented to demonstrate the value of the approach.