research-article

A Context-Aware Recommender System for Extended Software Product Line Configurations

Authors:

Juliana Alves Pereira,

Sandro Schulze,

Sebastian Krieter,

Márcio Ribeiro,

Gunter SaakeAuthors Info & Claims

VAMOS '18: Proceedings of the 12th International Workshop on Variability Modelling of Software-Intensive Systems

Pages 97 - 104

https://doi.org/10.1145/3168365.3168373

Published: 07 February 2018 Publication History

Abstract

Mass customization of standardized products has become a trend to succeed in today's market environment. Software Product Lines (SPLs) address this trend by describing a family of software products that share a common set of features. However, choosing the appropriate set of features that matches a user's individual interests is hampered due to the overwhelming amount of possible SPL configurations. Recommender systems can address this challenge by filtering the number of configurations and suggesting a suitable set of features for the user's requirements. In this paper, we propose a context-aware recommender system for predicting feature selections in an extended SPL configuration scenario, i.e. taking nonfunctional properties of features into consideration. We present an empirical evaluation based on a large real-world dataset of configurations derived from industrial experience in the Enterprise Resource Planning domain. Our results indicate significant improvements in the predictive accuracy of our context-aware recommendation approach over a state-of-the-art binary-based approach.

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Cited By

Heß TKarrer SOstheimer L(2024)Multi-Version Decision Propagation for Configuring Feature Models in Space and TimeProceedings of the 28th ACM International Systems and Software Product Line Conference10.1145/3646548.3676550(88-92)Online publication date: 2-Sep-2024
https://dl.acm.org/doi/10.1145/3646548.3676550
Shatnawi HSaquer JLo DGamess E(2024)Encoding Feature Models in Neo4j Graph DatabaseProceedings of the 2024 ACM Southeast Conference10.1145/3603287.3651199(157-166)Online publication date: 18-Apr-2024
https://dl.acm.org/doi/10.1145/3603287.3651199
Guégain ETaherkordi AQuinton C(2023)ICO: A Platform for Optimizing Highly Configurable Systems2023 38th IEEE/ACM International Conference on Automated Software Engineering Workshops (ASEW)10.1109/ASEW60602.2023.00013(62-67)Online publication date: 11-Sep-2023
https://doi.org/10.1109/ASEW60602.2023.00013
Show More Cited By

Index Terms

A Context-Aware Recommender System for Extended Software Product Line Configurations
1. Software and its engineering
  1. Software creation and management
    1. Software development techniques
      1. Reusability
        Software product lines
  2. Software organization and properties
    1. Extra-functional properties
    2. Software functional properties

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VAMOS '18: Proceedings of the 12th International Workshop on Variability Modelling of Software-Intensive Systems

February 2018

128 pages

ISBN:9781450353984

DOI:10.1145/3168365

Copyright © 2018 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

In-Cooperation

Universidad Politécnica de Madrid
URJC: Rey Juan Carlos University

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 07 February 2018

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VAMOS 2018

VAMOS 2018: 12th International Workshop on Variability Modelling of Software-Intensive Systems

February 7 - 9, 2018

Madrid, Spain

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VAMOS '18 Paper Acceptance Rate 15 of 34 submissions, 44%;

Overall Acceptance Rate 66 of 147 submissions, 45%

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Cited By

Heß TKarrer SOstheimer L(2024)Multi-Version Decision Propagation for Configuring Feature Models in Space and TimeProceedings of the 28th ACM International Systems and Software Product Line Conference10.1145/3646548.3676550(88-92)Online publication date: 2-Sep-2024
https://dl.acm.org/doi/10.1145/3646548.3676550
Shatnawi HSaquer JLo DGamess E(2024)Encoding Feature Models in Neo4j Graph DatabaseProceedings of the 2024 ACM Southeast Conference10.1145/3603287.3651199(157-166)Online publication date: 18-Apr-2024
https://dl.acm.org/doi/10.1145/3603287.3651199
Guégain ETaherkordi AQuinton C(2023)ICO: A Platform for Optimizing Highly Configurable Systems2023 38th IEEE/ACM International Conference on Automated Software Engineering Workshops (ASEW)10.1109/ASEW60602.2023.00013(62-67)Online publication date: 11-Sep-2023
https://doi.org/10.1109/ASEW60602.2023.00013
Shilov NOthman WFellmann MSandkuhl K(2023)Machine learning for enterprise modeling assistance: an investigation of the potential and proof of conceptSoftware and Systems Modeling10.1007/s10270-022-01077-y22:2(619-646)Online publication date: 6-Jan-2023
https://doi.org/10.1007/s10270-022-01077-y
Zanon ARocha LManzato M(2022)Balancing the trade-off between accuracy and diversity in recommender systems with personalized explanations based on Linked Open DataKnowledge-Based Systems10.1016/j.knosys.2022.109333252:COnline publication date: 27-Sep-2022
https://dl.acm.org/doi/10.1016/j.knosys.2022.109333
Nieke MSampaio GThüm TSeidl CTeixeira LSchaefer I(2021)Guiding the evolution of product-line configurationsSoftware and Systems Modeling (SoSyM)10.1007/s10270-021-00906-w21:1(225-247)Online publication date: 4-Jul-2021
https://dl.acm.org/doi/10.1007/s10270-021-00906-w
Shilov NOthman WFellmann MSandkuhl K(2021)Machine Learning-Based Enterprise Modeling Assistance: Approach and PotentialsThe Practice of Enterprise Modeling10.1007/978-3-030-91279-6_2(19-33)Online publication date: 11-Nov-2021
https://doi.org/10.1007/978-3-030-91279-6_2
Rodas-Silva JGalindo JGarcía-Gutiérrez JBenavides D(2019)RESDECProceedings of the 23rd International Systems and Software Product Line Conference - Volume B10.1145/3307630.3342390(33-36)Online publication date: 9-Sep-2019
https://dl.acm.org/doi/10.1145/3307630.3342390
Rodas-Silva JGalindo JGarcia-Gutierrez JBenavides D(2019)Selection of Software Product Line Implementation Components Using Recommender Systems: An Application to WordpressIEEE Access10.1109/ACCESS.2019.29184697(69226-69245)Online publication date: 2019
https://doi.org/10.1109/ACCESS.2019.2918469
Gonzalez-Fernandez YHamidi SChen SLiaskos S(2019)Efficient elicitation of software configurations using crowd preferences and domain knowledgeAutomated Software Engineering10.1007/s10515-018-0247-426:1(87-123)Online publication date: 1-Mar-2019
https://dl.acm.org/doi/10.1007/s10515-018-0247-4
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