research-article

Investigating the safe evolution of software product lines

Authors:

Leopoldo Teixeira,

Dem�stenes Sena,

Uir� Kulesza,

Paulo BorbaAuthors Info & Claims

GPCE '11: Proceedings of the 10th ACM international conference on Generative programming and component engineering

Pages 33 - 42

https://doi.org/10.1145/2047862.2047869

Published: 22 October 2011 Publication History

Abstract

The adoption of a product line strategy can bring significant productivity and time to market improvements. However, evolving a product line is risky because it might impact many products and their users. So when evolving a product line to introduce new features or to improve its design, it is important to make sure that the behavior of existing products is not affected. In fact, to preserve the behavior of existing products one usually has to analyze different artifacts, like feature models, configuration knowledge and the product line core assets. To better understand this process, in this paper we discover and analyze concrete product line evolution scenarios and, based on the results of this study, we describe a number of safe evolution templates that developers can use when working with product lines. For each template, we show examples of their use in existing product lines. We evaluate the templates by also analyzing the evolution history of two different product lines and demonstrating that they can express the corresponding modifications and then help to avoid the mistakes that we identified during our analysis.

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Cited By

Kr�ger JLi YLossev KZhu CChechik MBerger TRubin J(2024)A Meta-Study of Software-Change IntentionsACM Computing Surveys10.1145/3661484Online publication date: 25-Apr-2024
https://doi.org/10.1145/3661484
Motzfeldt IYu IDin CPun VStolz V(2023)Modular Soundness Checking of Feature Model Evolution PlansTheoretical Aspects of Computing – ICTAC 202310.1007/978-3-031-47963-2_25(417-437)Online publication date: 4-Dec-2023
https://dl.acm.org/doi/10.1007/978-3-031-47963-2_25
Michelon GAssunção WObermann DLinsbauer LGrünbacher PEgyed ATilevich EDe Roover C(2021)The life cycle of features in highly-configurable software systems evolving in space and timeProceedings of the 20th ACM SIGPLAN International Conference on Generative Programming: Concepts and Experiences10.1145/3486609.3487195(2-15)Online publication date: 17-Oct-2021
https://dl.acm.org/doi/10.1145/3486609.3487195
Show More Cited By

Index Terms

Investigating the safe evolution of software product lines
1. Software and its engineering
  1. Software creation and management
    1. Software post-development issues
      1. Software reverse engineering
  2. Software notations and tools
    1. Context specific languages
      1. Domain specific languages

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Published In

cover image ACM Conferences

GPCE '11: Proceedings of the 10th ACM international conference on Generative programming and component engineering

October 2011

194 pages

ISBN:9781450306898

DOI:10.1145/2047862

General Chair:
Ewen Denney
SGT/NASA Ames, USA
,
Program Chair:
Ulrik Pagh Schultz
University of Southern Denmark, Denmark

ACM SIGPLAN Notices Volume 47, Issue 3
GCPE '11
March 2012
179 pages
ISSN:0362-1340
EISSN:1558-1160
DOI:10.1145/2189751
Issue’s Table of Contents

Copyright © 2011 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]

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SIGPLAN: ACM Special Interest Group on Programming Languages

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 22 October 2011

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GPCE '11

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SIGPLAN

GPCE '11: Generative Programming and Component Engineering

October 22 - 23, 2011

Oregon, Portland, USA

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Overall Acceptance Rate 56 of 180 submissions, 31%

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Cited By

Krüger JLi YLossev KZhu CChechik MBerger TRubin J(2024)A Meta-Study of Software-Change IntentionsACM Computing Surveys10.1145/3661484Online publication date: 25-Apr-2024
https://doi.org/10.1145/3661484
Motzfeldt IYu IDin CPun VStolz V(2023)Modular Soundness Checking of Feature Model Evolution PlansTheoretical Aspects of Computing – ICTAC 202310.1007/978-3-031-47963-2_25(417-437)Online publication date: 4-Dec-2023
https://dl.acm.org/doi/10.1007/978-3-031-47963-2_25
Michelon GAssunção WObermann DLinsbauer LGrünbacher PEgyed ATilevich EDe Roover C(2021)The life cycle of features in highly-configurable software systems evolving in space and timeProceedings of the 20th ACM SIGPLAN International Conference on Generative Programming: Concepts and Experiences10.1145/3486609.3487195(2-15)Online publication date: 17-Oct-2021
https://dl.acm.org/doi/10.1145/3486609.3487195
Castro TTeixeira LAlves VApel SCordy MGheyi R(2021)A Formal Framework of Software Product Line AnalysesACM Transactions on Software Engineering and Methodology10.1145/344238930:3(1-37)Online publication date: 23-Apr-2021
https://dl.acm.org/doi/10.1145/3442389
Quinton CVierhauser MRabiser RBaresi LGrünbacher PSchuhmayer C(2021)Evolution in dynamic software product linesJournal of Software: Evolution and Process10.1002/smr.229333:2Online publication date: 14-Feb-2021
https://dl.acm.org/doi/10.1002/smr.2293
Nieke MMauro JSeidl CTh�m TYu IFranzke F(2020)Anomaly analyses for feature-model evolutionACM SIGPLAN Notices10.1145/3393934.327812353:9(188-201)Online publication date: 7-Apr-2020
https://dl.acm.org/doi/10.1145/3393934.3278123
Hoff ANieke MSeidl CS�ther EMotzfeldt IDin CYu ISchaefer ILopez-Herrejon R(2020)Consistency-preserving evolution planning on feature modelsProceedings of the 24th ACM Conference on Systems and Software Product Line: Volume A - Volume A10.1145/3382025.3414964(1-12)Online publication date: 19-Oct-2020
https://dl.acm.org/doi/10.1145/3382025.3414964
Hinterreiter DNieke MLinsbauer LSeidl CPr�hofer HGr�nbacher PSchaefer IReichenbach CStorm T(2019)Harmonized temporal feature modeling to uniformly perform, track, analyze, and replay software product line evolutionProceedings of the 18th ACM SIGPLAN International Conference on Generative Programming: Concepts and Experiences10.1145/3357765.3359515(115-128)Online publication date: 21-Oct-2019
https://dl.acm.org/doi/10.1145/3357765.3359515
Nieke MMauro JSeidl CTh�m TYu IFranzke FVan Wyk ERompf T(2018)Anomaly analyses for feature-model evolutionProceedings of the 17th ACM SIGPLAN International Conference on Generative Programming: Concepts and Experiences10.1145/3278122.3278123(188-201)Online publication date: 5-Nov-2018
https://dl.acm.org/doi/10.1145/3278122.3278123
Kr�her CGerling LSchmid K(2018)Identifying the intensity of variability changes in software product line evolutionProceedings of the 22nd International Systems and Software Product Line Conference - Volume 110.1145/3233027.3233032(54-64)Online publication date: 10-Sep-2018
https://dl.acm.org/doi/10.1145/3233027.3233032
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