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 ABSTRACT
The increasing importance being placed on software measurement
has led to an increased amount of research developing new software
measures. Given the importance of object-oriented development
techniques, one specific area where this has occurred is cohesion
measurement in object-oriented systems. However, despite a very
interesting body of work, there is little understanding of the
motivation and empirical hypotheses behind many of these new
measures. It is often difficult to determine how such measures
relate to one another and for which application they can be used.
As a consequence, it is very difficult for practitioners and
researchers to obtain a clear picture of the state-of-the-art
in order to select or define cohesion measures for object-oriented
systems. This situation is addressed and clarified through several
different activities. First, a standardized terminology and formalism
for expressing measures is provided which ensures that all measures
using it are expressed in a fully consistent and operational
manner. Second, to provide a structured synthesis, a review of
the existing approaches to measure cohesion in object-oriented
systems takes place. Third, a unified framework, based on the
issues discovered in the review, is provided and all existing
measures are then classified according to this framework. Finally,
a review of the empirical validation work concerning existing
cohesion measures is provided. This paper contributes to an
increased understanding of the state-of-the-art: a mechanism
is provided for comparing measures and their potential use, integrating
existing measures which examine the same concepts in different
ways, and facilitating more rigorous decision making regarding
the definition of new measures and the selection of existing
measures for a specific goal of measurement. In addition, our
review 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 models
as recommended by measurement theory, and (iii) an even smaller
number of measures have been empirically validated; thus, the
usefulness of many measures has yet to be demonstrated.
REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
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L. Briand , E. Arisholm , S. Counsell , F. Houdek , P. Thévenod--fosse, Empirical Studies of Object-Oriented Artifacts, Methods,and Processes: State of the Art and Future Directions, Empirical Software Engineering, v.4 n.4, p.387-404, December 1999
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Cara Stein , Letha Etzkorn , Sampson Gholston , Phillip Farrington , Dawn Utley , Glenn Cox , Julie Fortune, SEMANTIC METRICS: METRICS BASED ON SEMANTIC ASPECTS OF SOFTWARE, Applied Artificial Intelligence, v.23 n.1, p.44-77, January 2009
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