Paper Info
Title
Software requirement optimization using a multiobjective swarm intelligence evolutionary algorithm
Abstract
The selection of the new requirements which should be included in the development of the release of a software product is an important issue for software companies. This problem is known in the literature as the Next Release Problem (NRP). It is an NP-hard problem which simultaneously addresses two apparently contradictory objectives: the total cost of including the selected requirements in the next release of the software package, and the overall satisfaction of a set of customers who have different opinions about the priorities which should be given to the requirements, and also have different levels of importance within the company. Moreover, in the case of managing real instances of the problem, the proposed solutions have to satisfy certain interaction constraints which arise among some requirements. In this paper, the NRP is formulated as a multiobjective optimization problem with two objectives (cost and satisfaction) and three constraints (types of interactions). A multiobjective swarm intelligence metaheuristic is proposed to solve two real instances generated from data provided by experts. Analysis of the results showed that the proposed algorithm can efficiently generate high quality solutions. These were evaluated by comparing them with different proposals (in terms of multiobjective metrics). The results generated by the present approach surpass those generated in other relevant work in the literature (e.g. our technique can obtain a HV of over 60% for the most complex dataset managed, while the other approaches published cannot obtain an HV of more than 40% for the same dataset).
Year
DOI
Venue
2015
10.1016/j.knosys.2015.03.012
Knowledge-Based Systems
Keywords
Field
DocType
Next release problem,Multiobjective evolutionary algorithm,Software requirement selection,Search-based software engineering,Swarm intelligence,Artificial bee colony
Data mining,Evolutionary algorithm,Computer science,Swarm intelligence,Software,Artificial intelligence,Metaheuristic,Software requirements,Mathematical optimization,Multiobjective optimization problem,Total cost,Machine learning,Search-based software engineering
Journal
Volume
Issue
ISSN
83
C
0950-7051
Citations 
PageRank 
References 
1
0.35
26
Authors
3
Name
Order
Citations
PageRank
José M. Chaves-gonzález111912.16
Miguel A. Pérez-Toledano2261.70
Amparo Navasa Martínez310.35