1. Solving crosscutting concerns identification problem in object-oriented software with genetic algorithm
Authors : Richa Singh
Pages : 461-470
DOI : http://dx.doi.org/10.21172/1.71.065
Keywords : Aspect Mining, Crosscutting Concern Identification, Genetic Algorithm, Object-Oriented Software, Aspect oriented programming(AOP). Abstract :Identifying crosscutting concerns in existing developed software systems is a well known problem. This problem is known as aspect mining and is useful in reverse engineering as well as refactoring the concerns into Aspect Oriented Programming (AOP). Refactoring the existing system using AOP suffices the goal of making the existing system easier to maintain and evolve. Discovering crosscutting concerns from existing object oriented software by facilitating semi automated system is the main issue. To address this issue, proposed technique provides a solution using genetic algorithm (GA) based on the concept of traditional method invocations. In this work, it is found that proposed experiments based on genetic algorithm resulted in keeping the number of identified crosscutting concerns seeds high. The proposed technique also find out that the proposed solution worked well on standard benchmark case studies previously used in aspect mining.
Citing this Journal Article :Richa Singh, "Solving crosscutting concerns identification problem in object-oriented software with genetic algorithm", Volume 7 Issue 1 - May 2016, 461-470
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