Evolutionary Approaches for Multi-Objective Next Release Problem

Authors

  • Xinye Cai College of Computer Sciences and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, Jiangsu 210016
  • Ou Wei College of Computer Sciences and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, Jiangsu 210016
  • Zhiqiu Huang College of Computer Sciences and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, Jiangsu 210016

Keywords:

Multi-objective evolutionary optimization, multi-objective next release problem, requirement dependency, requirement engineering, software engineering

Abstract

In software industry, a common problem that the companies face is to decide what requirements should be implemented in the next release of the software. This paper aims to address the multi-objective next release problem using search based methods such as multi-objective evolutionary algorithms for empirical studies. In order to achieve the above goal, a requirement-dependency-based multi-objective next release model (MONRP/RD) is formulated firstly. The two objectives we are interested in are customers' satisfaction and requirement cost. A popular multi-objective evolutionary approach (MOEA), NSGA-II, is applied to provide the feasible solutions that balance between the two objectives aimed. The scalability of the formulated MONRP/RD and the influence of the requirement dependencies are investigated through simulations as well. This paper proposes an improved version of the multi-objective invasive weed optimization and compares it with various state-of-the-art multi-objective approaches on both synthetic and real-world data sets to find the most suitable algorithm for the problem.

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Published

2012-10-03

How to Cite

Cai, X., Wei, O., & Huang, Z. (2012). Evolutionary Approaches for Multi-Objective Next Release Problem. COMPUTING AND INFORMATICS, 31(4), 847–875. Retrieved from http://www.cai.sk/ojs/index.php/cai/article/view/1108