skip to main content
10.1145/3546932.3547006acmconferencesArticle/Chapter ViewAbstractPublication PagessplcConference Proceedingsconference-collections
research-article

Improving the customization of software product lines through the definition of local features

Published:12 September 2022Publication History

ABSTRACT

Variability in software product lines (SPL) is mostly described with feature models. In basic feature models, the selection of a feature for a particular product determines whether or not the feature is present in the product in a global manner. Even though there are cardinality-based feature models that allow a subset of features to be specified a number of times for each product, it is not possible to customize each instance of the feature with specific details for different elements of the product.

Some SPLs integrate model transformations and use domain specific languages to describe elements of the application that cannot be described using features (for example, the definition of the data model for a particular product). In this context, a stakeholder may require some features to be applied to some elements of the data model, but not globally (for example, not every entity in the data model may require an edition form). However, current feature models do not allow the stakeholder to specify this information.

In this paper, we propose a solution that solves this problem using domain-specific languages. In addition to defining global features for the entire application, our proposal allows the stakeholder to define local features that are specific to some elements such as parts of the application or specific entities of the data model and, using the DSL to define the product, those local features can be assigned to these elements or entities. This specification of the scope of application of features opens the door to a higher degree of customization of the generated products, thus improving their quality.

References

  1. Mauricio Alférez, Mathieu Acher, José A. Galindo, Benoit Baudry, and David Benavides. 2019. Modeling variability in the video domain: language and experience report. Vol. 27. 307--347 pages. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Suilen Alvarado, Alejandro Cortiñas, Miguel Luaces, Oscar Pedreira, and Ángeles Saavedra Places. 2020. Developing Web-based Geographic Information Systems with a DSL: Proposal and Case Study. Journal of Web Engineering (06 2020). Google ScholarGoogle ScholarCross RefCross Ref
  3. Sven Apel and Christian Kästner. 2009. An overview of feature-oriented software development. Journal of Object Technology 8, 5 (2009), 49--84. Google ScholarGoogle ScholarCross RefCross Ref
  4. Don Batory, David Benavides, and Antonio Ruiz-Cortes. 2006. Automated analysis of feature models: Challenges ahead. Commun. ACM 49, 12 (2006), 2--3. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. David Benavides, Sergio Segura, and Antonio Ruiz-Cortés. 2010. Automated analysis of feature models 20 years later: A literature review. Information Systems 35, 6 (sep 2010), 615--636. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. David Benavides, Pablo Trinidad, and Antonio Ruiz-Cortés. 2005. Automated Reasoning on Feature Models. In Proceedings of the 17th International Conference on Advanced Information Systems Engineering (CAiSE 2005). 491--503. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. A. Cortiñas, M. R. Luaces, O. Pedreira, A. S. Places, and J. Perez. 2017. Web-based Geographic Information Systems SPLE: Domain Analysis and Experience Report. In Proc. 21st International Systems & Software Product Line Conference (SPLC 2017) Vol.1. Sevilla, 190--194.Google ScholarGoogle Scholar
  8. Krzysztof Czarnecki, Thomas Bednasch, Peter Unger, and Ulrich Eisenecker. 2002. Generative programming for embedded software: An industrial experience report. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2487 (oct 2002), 156--172. Google ScholarGoogle ScholarCross RefCross Ref
  9. Krzysztof Czarnecki, Simon Helsen, and Ulrich Eisenecker. 2004. Staged configuration using feature models. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 3154 (2004), 266--283. Google ScholarGoogle ScholarCross RefCross Ref
  10. Krzysztof Czarnecki, Simon Helsen, and Ulrich Eisenecker. 2005. Formalizing cardinality-based feature models and their specialization. Software Process: Improvement and Practice 10, 1 (jan 2005), 7--29. Google ScholarGoogle ScholarCross RefCross Ref
  11. Krzysztof Czarnecki, Simon Helsen, and Ulrich Eisenecker. 2005. Staged configuration through specialization and multilevel configuration of feature models. Software Process Improvement and Practice 10, 2 (2005), 143--169. Google ScholarGoogle ScholarCross RefCross Ref
  12. José A. Galindo and David Benavides. 2020. A Python framework for the automated analysis of feature models: A first step to integrate community efforts. ACM International Conference Proceeding Series Part F1644 (2020), 52--55. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. Jose-Miguel Horcas, Alejandro Cortiñas, Lidia Fuentes, and Miguel R Luaces. 2022. Combining multiple granularity variability in a software product line approach for web engineering. Information and Software Technology 148 (2022), 106910.Google ScholarGoogle ScholarCross RefCross Ref
  14. José Miguel Horcas, Mónica Pinto, and Lidia Fuentes. 2022. Empirical analysis of the tool support for software product lines. Software and Systems Modeling (2022). Google ScholarGoogle ScholarCross RefCross Ref
  15. Aitziber Iglesias, Markel Iglesias-Urkia, Beatriz López-Davalillo, Santiago Charramendieta, and Aitor Urbieta. 2019. Trilateral: Software product line based multidomain IoT artifact generation for industrial CPS. MODELSWARD 2019 - Proceedings of the 7th International Conference on Model-Driven Engineering and Software Development (2019), 64 -- 73. Cited by: 11; All Open Access, Hybrid Gold Open Access. Google ScholarGoogle ScholarCross RefCross Ref
  16. Kyo C Kang, Sholom G Cohen, James a Hess, William E Novak, and a Spencer Peterson. 1990. Feature-Oriented Domain Analysis (FODA) Feasibility Study. Software Engineering Institue 17, November (1990), 161. Google ScholarGoogle ScholarCross RefCross Ref
  17. Ahmet Serkan Karataş, Halit Oğuztüzün, and Ali Doğru. 2013. From extended feature models to constraint logic programming. Science of Computer Programming 78, 12 (2013), 2295--2312. Google ScholarGoogle ScholarCross RefCross Ref
  18. Klaus Pohl, Günter Böckle, and Frank Van Der Linden. 2005. Software Product Line Engineering: foundations, principles and techniques. Vol. 49. Springer Science & Business Media. 467 pages. Google ScholarGoogle ScholarCross RefCross Ref
  19. D. Ramos Vidal, A. Cortiñas, M. R. Luaces, O. Pedreira, and A. S. Places. 2020. A Software Product Line for Digital Libraries. In Proc of the 16th International Conference on Web Information Systems and Technologies (WEBIST 2020). Online, 321--334.Google ScholarGoogle Scholar
  20. M Riebisch, K Böllert, D Streitferdt, and I Philippow. 2002. Extending Feature Diagrams with UML Multiplicities. 6th World Conference on Integrated Design & Process Technology (2002), 1--7. http://www.citeulike.org/group/858/article/505058Google ScholarGoogle Scholar
  21. Luisa Rincon, Gabriel Rodriguez, Juan C. Martinez, Gloria Ines Alvarez, and Maria Constanza Pabon. 2015. Creating virtual stores using software product lines: An application case; [Caso de Aplicación para Crear Tiendas Virtuales Usando Lineas de Productos de Software]. 2015 10th Colombian Computing Conference, 10CCC 2015 (2015), 71 -- 78. Cited by: 1. Google ScholarGoogle ScholarCross RefCross Ref
  22. D.C. Sharp. 1998. Reducing avionics software cost through component based product line development. In 17th DASC. AIAA/IEEE/SAE. Digital Avionics Systems Conference. Proceedings (Cat. No.98CH36267), Vol. 2. G32/1--G32/8 vol.2. Google ScholarGoogle ScholarCross RefCross Ref
  23. Gustavo Sousa, Walter Rudametkin, and Laurence Duchien. 2016. Extending feature models with relative cardinalities. ACM International Conference Proceeding Series 16--23-September-2016 (2016), 79--88. Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. Salvador Trujillo, Don Batory, and Oscar Diaz. 2007. Feature Oriented Model Driven Development: A Case Study for Portlets. In Software Engineering, 2007. ICSE 2007. 29th International Conference on. IEEE, 44--53. Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. Markus Voelter and Eelco Visser. 2011. Product Line Engineering Using Domain-Specific Languages. In 2011 15th International Software Product Line Conference. 70--79. Google ScholarGoogle ScholarDigital LibraryDigital Library
  26. David M Weiss, Paul Clements, and Charles W Krueger. 2006. Software Product Line Hall of Fame. SPLC 2006: Proceedings of the 10th International Software Product Line Conference (2006), 237. Google ScholarGoogle ScholarCross RefCross Ref

Index Terms

  1. Improving the customization of software product lines through the definition of local features

        Recommendations

        Comments

        Login options

        Check if you have access through your login credentials or your institution to get full access on this article.

        Sign in
        • Published in

          cover image ACM Conferences
          SPLC '22: Proceedings of the 26th ACM International Systems and Software Product Line Conference - Volume A
          September 2022
          266 pages
          ISBN:9781450394437
          DOI:10.1145/3546932

          Copyright © 2022 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]

          Publisher

          Association for Computing Machinery

          New York, NY, United States

          Publication History

          • Published: 12 September 2022

          Permissions

          Request permissions about this article.

          Request Permissions

          Check for updates

          Qualifiers

          • research-article

          Acceptance Rates

          SPLC '22 Paper Acceptance Rate14of41submissions,34%Overall Acceptance Rate167of463submissions,36%

        PDF Format

        View or Download as a PDF file.

        PDF

        eReader

        View online with eReader.

        eReader