A conceptual model for unifying variability in space and time

Ananieva, Sofia; Greiner, Sandra; Kühn, Thomas; Krüger, Jacob; Linsbauer, Lukas; Grüner, Sten; Kehrer, Timo; Klare, Heiko; Koziolek, Anne; Lönn, Henrik; Thüm, Thomas; Seidl, Christoph; Ramesh, S.; Reussner, Ralf; Westfechtel, Bernhard

doi:10.1145/3382025.3414955

Cited by 28 publications

(21 citation statements)

References 58 publications

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“…To demonstrate feasibility, we implemented proof plans in the prototype KeYPl (KeY for Proof Plans). 2 We use the KeY verification system [? ] as underlying verification calculus and the Java modeling language (JML) [? ]…”

Section: Discussionmentioning

confidence: 99%

“…]. Finally, to compare 2 Prototype, case study, and results available at: https://github.com/ekuiter/KeYPl Besides the discussed strategies, there are two widely known SPL analysis strategies that are not representable as proof plans, namely feature-based verification [6] and family-based verification with metaproducts [35]: First, feature-based strategies verify each feature (in our context, each method) in isolation, ignoring all references to other features (here, all calls). In terms of proof graphs, this would mean conducting proofs only for the proof graph's source nodes, not for intermediate or sink nodes.…”

Section: Discussionmentioning

confidence: 99%

“…. In this scenario, we profit from proof reuse due to variability in space [2], as similar products share proofs.…”

Section: Applicationsmentioning

confidence: 99%

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Verification Strategies for Feature-Oriented Software Product Lines

Kuiter

Knüppel

Bordis

et al. 2022

Proceedings of the 16th International Working Conference on Variability Modelling of Software-Intensive Systems

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Highly-customizable software systems in form of software product lines are becoming increasingly relevant for safety-critical systems, in which the correctness of software is a major concern. To ensure the correct behavior of a software product line, each product can be verified in isolation-however, this strategy quickly becomes infeasible for a large number of products.In this paper, we propose proof plans, a novel strategy for verifying feature-oriented software product lines based on partial proofs. Our technique splits the verification task into small proofs that can be reused across method variants, which gives rise to a wider spectrum of verification strategies for software product lines. We describe applications of our technique and evaluate one of them on a case study by comparing it with established verification strategies. CCS CONCEPTS• Software and its engineering → Software product lines; Formal software verification.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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Verification Strategies for Feature-Oriented Software Product Lines

Kuiter

Knüppel

Bordis

et al. 2022

Proceedings of the 16th International Working Conference on Variability Modelling of Software-Intensive Systems

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“…Effectively managing the evolution of variant-rich software systems is still among the main challenges of software engineering [16], [17], though being tackled from many different angles. The terminology introduced by Antkiewicz et al [10] distinguishes seven levels in the continuum between ad-hoc clone-and-own (L0) and rigorous SPLE (L6).…”

Section: State-of-the-art and Research Gapsmentioning

confidence: 99%

Bridging the Gap Between Clone-and-Own and Software Product Lines

Kehrer

Thüm

SchultheiB

et al. 2021

2021 IEEE/ACM 43rd International Conference on Software Engineering: New Ideas and Emerging Results (ICSE-NIER)

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Software is often released in multiple variants to meet all customer requirements. While software product lines address this need by advocating the development of an integrated software platform, practitioners frequently rely on adhoc reuse based on a principle which is known as clone-andown. This practice avoids high up-front investments, as new variants of a software family are created by simply copying and adapting an existing variant, but maintenance costs explode once a critical number of variants is reached. With our research project VARIANTSYNC, we aim to bridge the gap between clone-and-own and product lines by combining the minimal overhead and flexibility of clone-and-own with the systematic handling of variability in software product lines. The key idea is to transparently integrate product-line concepts with variant management facilities known from version control systems in order to automatically synchronize a set of evolving variants. We believe that VARIANTSYNC has the potential to change the way how practitioners develop multi-variant software systems for which it is hard to foresee which variants will be added in the future.

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“…Product-line evolution is a well-acknowledged field and current field of research [8][9][10][11]. Similar to all other software systems, evolution of product lines is ubiquitous due to changed or new requirements.…”

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confidence: 99%

Guiding the evolution of product-line configurations

et al. 2021

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A product line is an approach for systematically managing configuration options of customizable systems, usually by means of features. Products are generated for configurations consisting of selected features. Product-line evolution can lead to unintended changes to product behavior. We illustrate that updating configurations after product-line evolution requires decisions of both, domain engineers responsible for product-line evolution as well as application engineers responsible for configurations. The challenge is that domain and application engineers might not be able to interact with each other. We propose a formal foundation and a methodology that enables domain engineers to guide application engineers through configuration evolution by sharing knowledge on product-line evolution and by defining automatic update operations for configurations. As an effect, we enable knowledge transfer between those engineers without the need for interactions. We evaluate our methodology on four large-scale industrial product lines. The results of the qualitative evaluation indicate that our method is flexible enough for real-world product-line evolution. The quantitative evaluation indicates that we detect product behavior changes for up to $$55.3\%$$ 55.3 % of the configurations which would not have been detected using existing methods.

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A conceptual model for unifying variability in space and time

Cited by 28 publications

References 58 publications

Verification Strategies for Feature-Oriented Software Product Lines

Verification Strategies for Feature-Oriented Software Product Lines

Bridging the Gap Between Clone-and-Own and Software Product Lines

Guiding the evolution of product-line configurations

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