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Incorporating User Preferences in Multi-objective Feature Selection in Software Product Lines Using Multi-Criteria Decision Analysis

  • Lero – The Irish Software Research Centre
  • University College Dublin
  • Dublin City University

Research output: Chapter in Book or Conference Publication/ProceedingConference Publicationpeer-review

2 Citations (Scopus)

Abstract

Software Product Lines Engineering has created various tools that assist with the standardisation in the design and implementation of clusters of equivalent software systems with an explicit representation of variability choices in the form of Feature Models, making the selection of the most ideal software product a Feature Selection problem. With the increase in the number of properties, the problem needs to be defined as a multi-objective optimisation where objectives are considered independently one from another with the goal of finding and providing decision-makers a large and diverse set of non-dominated solutions/products. Following the optimisation, decision-makers define their own (often complex) preferences on how does the ideal software product look like. Then, they select the unique solution that matches their preferences the most and discard the rest of the solutions—sometimes with the help of some Multi-Criteria Decision Analysis technique. In this work, we study the usability and the performance of incorporating preferences of decision-makers by carrying-out Multi-Criteria Decision Analysis directly within the multi-objective optimisation to increase the chances of finding more solutions that match preferences of the decision-makers the most and avoid wasting execution time searching for non-dominated solutions that are poor with respect to decision-makers’ preferences.

Original languageEnglish
Title of host publicationOptimization and Learning - 4th International Conference, OLA 2021, Proceedings
EditorsBernabé Dorronsoro, Patricia Ruiz, Lionel Amodeo, Mario Pavone
PublisherSpringer Science and Business Media Deutschland GmbH
Pages361-373
Number of pages13
ISBN (Print)9783030856717
DOIs
Publication statusPublished - 2021
Externally publishedYes
Event4th International Conference on Optimization and Learning, OLA 2021 - Virtual, Online
Duration: 21 Jun 202123 Jun 2021

Publication series

NameCommunications in Computer and Information Science
Volume1443
ISSN (Print)1865-0929
ISSN (Electronic)1865-0937

Conference

Conference4th International Conference on Optimization and Learning, OLA 2021
CityVirtual, Online
Period21/06/2123/06/21

Keywords

  • Feature selection
  • Multi-Criteria Decision Analysis
  • Multi-objective evolution algorithm
  • Software product line

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