Title
A study of the bi-objective next release problem
Abstract
One important issue addressed by software companies is to determine which features should be included in the next release of their products, in such a way that the highest possible number of customers get satisfied while entailing the minimum cost for the company. This problem is known as the Next Release Problem (NRP). Since minimizing the total cost of including new features into a software package and maximizing the total satisfaction of customers are contradictory objectives, the problem has a multi-objective nature. In this work, we apply three state-of-the-art multi-objective metaheuristics (two genetic algorithms, NSGA-II and MOCell, and one evolutionary strategy, PAES) for solving NRP. Our goal is twofold: on the one hand, we are interested in analyzing the results obtained by these metaheuristics over a benchmark composed of six academic problems plus a real world data set provided by Motorola; on the other hand, we want to provide insight about the solution to the problem. The obtained results show three different kinds of conclusions: NSGA-II is the technique computing the highest number of optimal solutions, MOCell provides the product manager with the widest range of different solutions, and PAES is the fastest technique (but with the least accurate results). Furthermore, we have observed that the best solutions found so far are composed of a high percentage of low-cost requirements and of those requirements that produce the largest satisfaction on the customers as well.
Year
DOI
Venue
2011
10.1007/s10664-010-9147-3
Empirical Software Engineering
Keywords
Field
DocType
Search based software engineering,Multi-objective optimization,Next release,Requirements engineering
Mathematical optimization,Computer science,Requirements engineering,Multi-objective optimization,Evolution strategy,Total cost,Test data generation,Genetic algorithm,Search-based software engineering,Metaheuristic
Journal
Volume
Issue
ISSN
16
1
1382-3256
Citations 
PageRank 
References 
33
1.30
41
Authors
5
Name
Order
Citations
PageRank
Juan J. Durillo174725.47
Yuanyuan Zhang260017.33
Enrique Alba33796242.34
Mark Harman410264389.82
Antonio J. Nebro5111854.62