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Software change impact analysis (CIA) is a key technique for identifying unpredicted and potential effects caused by changes made to software. Different change types often have different impact mechanisms, even some changes do not impact other entities in programs in spite of some dependences existed between these entities and the modified entity. In this paper, we propose a static CIA technique,...
Program call graph representation can be used to support many tasks in compiler optimization, program comprehension, and software maintenance. During software evolution, the call graph needs to remain fairly precise and be updated quickly in response to software changes. In this paper, we present an approach to incremental update, instead of exhaustive analysis of the initially constructed call graph...
Understanding software change patterns during evolution is important for researchers concerned with alleviating change impacts. It can provide insight to understand the software evolution, predict future changes, and develop new refactoring algorithms. However, most of the current research focus on the procedural programs like C, or object-oriented programs like Java; seldom effort has been made for...
In this paper, we propose a fine-grained coupling metrics suite for aspect-oriented (AO) systems, to measure software changes during system evolution. We also present a correlation model in terms of intermediate processes, for better evaluating the relation between coupling metrics and system maintainability. To investigate the practicability of our proposed model, we have implemented a coupling metrics...
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