A Unified Framework for Cohesion Measurement in Object-OrientedSystems

  • Authors:

  • Lionel C. Briand;John W. Daly;Jürgen Wüst

  • Affiliations:

  • Fraunhofer Institute for Experimental Software Engineering, Kaiserslautern, Germany. E-mail briand@iese.fhg.de;Fraunhofer Institute for Experimental Software Engineering, Kaiserslautern, Germany;Fraunhofer Institute for Experimental Software Engineering, Kaiserslautern, Germany. E-mail wuest@iese.fhg.de

  • Venue:
  • Empirical Software Engineering
  • Year:
  • 1998

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Abstract

The increasing importance being placed on software measurementhas led to an increased amount of research developing new softwaremeasures. Given the importance of object-oriented developmenttechniques, one specific area where this has occurred is cohesionmeasurement in object-oriented systems. However, despite a veryinteresting body of work, there is little understanding of themotivation and empirical hypotheses behind many of these newmeasures. It is often difficult to determine how such measuresrelate to one another and for which application they can be used.As a consequence, it is very difficult for practitioners andresearchers to obtain a clear picture of the state-of-the-artin order to select or define cohesion measures for object-orientedsystems. This situation is addressed and clarified through severaldifferent activities. First, a standardized terminology and formalismfor expressing measures is provided which ensures that all measuresusing it are expressed in a fully consistent and operationalmanner. Second, to provide a structured synthesis, a review ofthe existing approaches to measure cohesion in object-orientedsystems takes place. Third, a unified framework, based on theissues discovered in the review, is provided and all existingmeasures are then classified according to this framework. Finally,a review of the empirical validation work concerning existingcohesion measures is provided. This paper contributes to anincreased understanding of the state-of-the-art: a mechanismis provided for comparing measures and their potential use, integratingexisting measures which examine the same concepts in differentways, and facilitating more rigorous decision making regardingthe definition of new measures and the selection of existingmeasures for a specific goal of measurement. In addition, ourreview of the state-of-the-art highlights several important issues:(i) many measures are not defined in a fully operational form,(ii) relatively few of them are based on explicit empirical modelsas recommended by measurement theory, and (iii) an even smallernumber of measures have been empirically validated; thus, theusefulness of many measures has yet to be demonstrated.