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GRASP-Based Hybrid Search to Solve the Multi-objective Requirements Selection Problem

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Optimization and Learning (OLA 2022)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1684))

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Abstract

One of the most important and recurring issues that the development of a software product faces is the requirements selection problem. Addressing this issue is especially crucial if agile methodologies are used. The requirements selection problem, also called Next Release Problem (NRP), seeks to choose a subset of requirements which will be implemented in the next increment of the product. They must maximize clients satisfaction and minimize the cost or effort of implementation. This is a combinatorial optimization problem studied in the area of Search-Based Software Engineering. In this work, the performance of a basic genetic algorithm and a widely used multi-objective genetic algorithm (NSGA-II) have been compared against a multi-objective version of a randomized greedy algorithm (GRASP). The results obtained show that, while NSGA-II is frequently used to solve this problem, faster algorithms, such as GRASP, can return solutions of similar or even better quality using the proper configurations and search techniques. The repository with the code and analysis used in this study is made available to those interested via GitHub.

This work has been partially funded by the Regional Government (JCCM) and ERDF funds through the projects SBPLY/17/180501/000493 and SBPLY/21/180501/000148.

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Notes

  1. 1.

    Although “stakeholder” is a more appropriate term, “client” will be used to keep coherence with previous works present in the literature.

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Authors and Affiliations

  1. Department of Computing Systems, Intelligent Systems and Data Mining Laboratory (I3A), Universidad de Castilla-La Mancha, 02071, Albacete, Spain

    Víctor Pérez-Piqueras, Pablo Bermejo López & José A. Gámez

Authors
  1. Víctor Pérez-Piqueras
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  2. Pablo Bermejo López
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  3. José A. Gámez
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Corresponding author

Correspondence to Víctor Pérez-Piqueras .

Editor information

Editors and Affiliations

  1. Universidad de Cádiz, Cadiz, Spain

    Bernabé Dorronsoro

  2. University of Catania, Catania, Italy

    Mario Pavone

  3. University of Paris-Est, Paris, France

    Amir Nakib

  4. Université de Lille, Lille, France

    El-Ghazali Talbi

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Pérez-Piqueras, V., López, P.B., Gámez, J.A. (2022). GRASP-Based Hybrid Search to Solve the Multi-objective Requirements Selection Problem. In: Dorronsoro, B., Pavone, M., Nakib, A., Talbi, EG. (eds) Optimization and Learning. OLA 2022. Communications in Computer and Information Science, vol 1684. Springer, Cham. https://doi.org/10.1007/978-3-031-22039-5_15

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  • DOI: https://doi.org/10.1007/978-3-031-22039-5_15

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-22038-8

  • Online ISBN: 978-3-031-22039-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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