Using coupling measurement for impact analysis in object-oriented systems

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Abstract
Many coupling measures have been proposed in the context of object oriented (OO) systems. In addition, due to the numerous dependencies present in OO systems, several studies have highlighted the complexity of using dependency analysis to perform impact analysis. An alternative is to investigate the construction of probabilistic decision models based on coupling measurement to support impact analysis. In addition to providing an ordering of classes where ripple effects are more likely, such an approach is simple and can be automated. In our investigation, we perform a thorough analysis on a commercial C++ system where change data has been collected over several years. We identify the coupling dimensions that seem to be significantly related to ripple effects and use these dimensions to rank classes according to their probability of containing ripple effects. We then assess the expected effectiveness of such decision models.

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