Investigation of Risks in Reengineering Process Using Grey Wolf Optimization Algorithm
A. Cathreen Graciamary1, M. Chidambaram2

1A. Cathreen Graciamary, Research Scholar, Bharathiar University, Coimbatore (Tamil Nadu), India.
2Dr. M.Chidambaram, Asst Professor, Rajah Serofiji College, Thanjavur (Tamil Nadu), India.
Manuscript received on 01 May 2019 | Revised Manuscript received on 15 May 2019 | Manuscript published on 30 May 2019 | PP: 1644-1656 | Volume-8 Issue-7, May 2019 | Retrieval Number: G535505871919/19©BEIESP
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Abstract: One among the principal challenges in software frameworks construction in current days will be quality and functionality. The concept of forecasting the quality of a software product from the higher-level formulation explanation is not the fresh strategy. Software Reengineering is the process of maintaining the software to suit the requirements provided by the user. There will be lot of risks associated with the process of Reengineering.Especially the process of Reengineering encounters the quality and functionality risks. This means that while performing the process of Reengineering failure to maintain the quality and functionality of original system.The utilization of soft computing intelligence strategies to evaluate the risks is the freshly researched area. The term “risk” in developing the conclusions will be customarily utilizedinreplicateambiguitywhich might be considered probabilistically. Here in to analyze the risks involved in the process of Reengineering nature inspired Grey Wolf optimization Techniques is used. By employing the Grey wolf optimization techniques in evaluation of risks in the process of reengineering, searches effectively and identifies the quality risks effectively rather than functionality risks. Though Grey Wolf Optimization algorithm techniques have very good exploration techniques its performance in analyzing the risks associated with functionality risks in reengineering will be little be lower when compared with risks associated with quality risks. Experimental results demonstrated that evaluation of quality risks associated in the process of reengineering process is exceptionally well.
Keyword: Reengineering, Legacy Systems, Quality Risks, Functionality Risks, Meta Heuristics, Grey Wolf Technique.
Scope of the Article: Discrete Optimization.