• DocumentCode
    3342765
  • Title

    MoJo: a distance metric for software clusterings

  • Author

    Tzerpos, Vassilios ; Holt, R.C.

  • Author_Institution
    Toronto Univ., Ont., Canada
  • fYear
    1999
  • fDate
    6-8 Oct 1999
  • Firstpage
    187
  • Lastpage
    193
  • Abstract
    The software clustering problem has attracted much attention recently, since it is an integral part of the process of reverse engineering large software systems. A key problem in this research is the difficulty in comparing different approaches in an objective fashion. In this paper, we present a metric, called MoJo (Move-Join), that can be used in evaluating the similarity of two different decompositions of a software system. Our metric calculates a distance between two partitions of the same set of software resources. We begin by introducing the model we use. Then we present a heuristic algorithm that calculates the distance in an efficient fashion. Finally, we discuss some experiments that showcase the performance of the algorithm and the effectiveness of the metric
  • Keywords
    heuristic programming; reverse engineering; software metrics; software performance evaluation; MoJo software metric; algorithm performance; cluster joining; cluster moving; distance metric; heuristic algorithm; large software systems; reverse engineering; software clusterings; software resource partitioning; software system dcomposition; Electrical capacitance tomography; Feedback; Hardware; Reverse engineering; Software measurement; Software systems; System testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Reverse Engineering, 1999. Proceedings. Sixth Working Conference on
  • Conference_Location
    Atlanta, GA
  • Print_ISBN
    0-7695-0303-9
  • Type

    conf

  • DOI
    10.1109/WCRE.1999.806959
  • Filename
    806959