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A study of the bi-objective next release problem

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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.

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Acknowledgements

J. J. Durillo, A. Nebro, and E. Alba acknowledge founds from the “Consejería de Innovación, Ciencia y Empresa”, Junta de Andalucía under contract P07-TIC-03044 DIRICOM project (http://diricom.lcc.uma.es), and the Spanish Ministry of Science and Innovation and FEDER under contract TIN2008-06491-C04-01 (the M* project). J. J. Durillo is also supported by grant AP-2006-03349 from the Spanish Ministry of Education and Science. Mark Harman is partly supported by EPSRC grants EP/G060525 (CREST: Centre for Research on Evolution, Search and Testing, Platform Grant), and EP/D050863 (SEBASE: Software Engineering By Automated SEarch), which also fully supports Yuanyuan Zhang.

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Authors and Affiliations

  1. Computer Science Department, University of Málaga, Málaga, Spain

    Juan J. Durillo, Enrique Alba & Antonio J. Nebro

  2. CREST Centre, University College London, London, UK

    Yuanyuan Zhang & Mark Harman

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  1. Juan J. Durillo
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  2. Yuanyuan Zhang
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  3. Enrique Alba
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  4. Mark Harman
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  5. Antonio J. Nebro
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Correspondence to Juan J. Durillo.

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Editors: Simon Poulding and Massimiliano Di Penta

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Durillo, J.J., Zhang, Y., Alba, E. et al. A study of the bi-objective next release problem. Empir Software Eng 16, 29–60 (2011). https://doi.org/10.1007/s10664-010-9147-3

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