A unified framework for coupling measurement in object-oriented systems

Citation
Lc. Briand et al., A unified framework for coupling measurement in object-oriented systems, IEEE SOFT E, 25(1), 1999, pp. 91-121
Citations number
39
Categorie Soggetti
Computer Science & Engineering
Journal title
IEEE TRANSACTIONS ON SOFTWARE ENGINEERING
ISSN journal
00985589 → ACNP
Volume
25
Issue
1
Year of publication
1999
Pages
91 - 121
Database
ISI
SICI code
0098-5589(199901/02)25:1<91:AUFFCM>2.0.ZU;2-U
Abstract
The increasing importance being placed on software measurement has led to a n increased amount of research developing new software measures. Given the importance of object-oriented development techniques, one specific area whe re this has occurred is coupling measurement in object-oriented systems. Ho wever, despite a very interesting and rich body of work, there is little un derstanding 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 measures for o bject-oriented systems. This situation is addressed and clarified through several different activit ies. First, a standardized terminology and formalism for expressing measure s is provided which ensures that all measures using it are expressed in a f ully consistent and operational manner. Second, to provide a structured syn thesis, a review of the existing frameworks and measures for coupling measu rement 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. This paper contributes to an increased understanding of the state-of-the-ar t: 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 definiti on of new measures and the selection of existing measures for a specific go al of measurement. In addition, our review of the state-of-the-art highligh ts that many measures are not defined in a fully operational form, and rela tively few of them are based on explicit empirical models, as recommended b y measurement theory.