期刊名称：International Journal of Computer Science and Information Technologies
电子版ISSN：0975-9646
出版年度：2015
卷号：6
期号：6
页码：5004-5013
出版社：TechScience Publications
摘要：While developing a software system, the complexity in describing a problem should be reduced. This can be done by separating the concern in a clean and explicit way. Each of the concern can be addressed by partitioning a software system into modules. Concerns are clearly identifiable with a special linguistic construct called Aspects, which has been introduced by a new programming paradigm known as aspect-oriented programming. No doubt aspect-oriented programming brings lots of opportunities for the software developer. On the other hand, it is very difficult for analysing those programs for different software engineering activities. In such scenario, slicing plays a vital role. This paper proposes an approach to compute the dynamic slices of aspect-oriented programs. In our approach, we have introduced different level dependence graphs, such as aspectoriented statement level dependence graph, aspect-oriented method level dependence graph, aspect-oriented AC weaving level dependence graph, aspect-oriented package level dependence graph to represent an aspect-oriented program under consideration. Then, we apply aspect-oriented reverse hierarchical dynamic slicing algorithm on the intermediate program representation to compute the dynamic slices. Our algorithm traverses the dependence edges starting from the slicing node in a reverse hierarchical manner to list the reached node, which constitute the dynamic slice of the aspect-oriented program under consideration. This approach is advantageous as it constructs the graph and computes the dynamic slices level wise. At a particular instance the level dependence graph is quite manageable and quickly traversed. It can also generate intermediate slices moving from the statement level to package level. The space complexity of our algorithm is O(n2 ), where n is the total number of nodes in the graph and time complexity is O(n2 ), Where n is the total number of executed statements in the execution trace of the program
