Harmonized temporal feature modeling to uniformly perform, track, analyze, and replay software product line evolution

Hinterreiter, Daniel; Nieke, Michael; Linsbauer, Lukas; Seidl, Christoph; Prähofer, Herbert; Grünbacher, Paul

doi:10.1145/3357765.3359515

Cited by 16 publications

(14 citation statements)

References 32 publications

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“…To the best of our knowledge, there are no existing studies on feature location techniques and feature models taking into account feature revisions. As mentioned by Hinterreiter et al [11] it is essential to consider feature revisions in an SPL because features are constantly evolving. In this way, we contribute with the state of the art to mitigate this new assumption to treat revisions of features.…”

Section: Preliminary Resultsmentioning

confidence: 99%

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Evolving System Families in Space and Time

Michelon

2020

Proceedings of the 24th ACM International Systems and Software Product Line Conference - Volume B

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Managing the evolution of system families in space and time, i.e., system variants and their revisions is still an open challenge. The software product line (SPL) approach can support the management of product variants in space by reusing a common set of features. However, feature changes over time are often necessary due to adaptations and/or bug fixes, leading to different product versions. Such changes are commonly tracked in version control systems (VCSs). However, VCSs only deal with the change history of source code, and, even though their branching mechanisms allow to develop features in isolation, VCS does not allow propagating changes across variants. Variation control systems have been developed to support more fine-grained management of variants and to allow tracking of changes at the level of files or features. However, these systems are also limited regarding the types and granularity of artifacts. Also, they are cognitively very demanding with increasing numbers of revisions and variants. Furthermore, propagating specific changes over variants of a system is still a complex task that also depends on the variability-aware change impacts. Based on these existing limitations, the goal of this doctoral work is to investigate and define a flexible and unified approach to allow an easy and scalable evolution of SPLs in space and time. The expected contributions will aid the management of SPL products and support engineers to reason about the potential impact of changes during SPL evolution. To evaluate the approach, we plan to conduct case studies with real-world SPLs.

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Section: Preliminary Resultsmentioning

confidence: 99%

“…We are just at the beginning of this step. Thus, our next task is to survey the literature on existing (temporal) feature modeling approaches [11]. Next, we will select a strategy for implementing feature revision models.…”

Section: Implementation Aspectsmentioning

confidence: 99%

Evolving System Families in Space and Time

Michelon

2020

Proceedings of the 24th ACM International Systems and Software Product Line Conference - Volume B

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“…Feature models. We use a temporal feature modeling approach (Hinterreiter et al, 2019) with support for grouping features in components and arranging them in different modeling spaces as described in (Rabiser et al, 2018). An important extension to other feature modeling approaches is to support feature model evolution as we will describe in the next section.…”

Section: Platform Elementsmentioning

confidence: 99%

“…Basic feature modeling techniques do not support continuous evolution and versioning by tracking the evolution of features model and mapped artifacts over time. We thus extended our approach with temporal feature modeling (Hinterreiter et al, 2019) to also manage revisions of features and feature models. Each change to a feature model is tracked by creating a new revision of the feature model as well as new revisions for the changed features.…”

Section: Temporal Feature Modelingmentioning

confidence: 99%

Supporting feature-oriented evolution in industrial automation product lines

Hinterreiter

Linsbauer

Feichtinger

et al. 2020

Concurrent Engineering

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In the domain of industrial automation companies nowadays need to serve a mass market while at the same time customers demand highly customized solutions. To tackle this problem, companies frequently define software product lines (SPLs), which allow to automatically derive and further customize individual solutions based on a common platform. SPLs rely on defining common and variable platform features together with mappings, which define how the features are realized in implementation artifacts. In concurrent engineering such a feature-oriented process is challenged by the evolution of features, the complexity of feature-to-artifact mappings, and the diversity of the implementation artifacts. To address these challenges this paper introduces an approach supporting feature-oriented development and evolution in industrial SPLs. We outline the key elements and operations of our approach, including an implementation in a development environment. We report results of evaluating our approach regarding functional correctness, usefulness, and scalability based on a case study of a Pick-and-Place Unit (PPU) and an industrial case system.

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“…While there is existing work on a common variability meta-model (e.g., Haugen Figure 2: Key components of an approach for transforming variability models. et al [25], Hinterreiter et al [26], Schobbens et al [37], Sepúlveda et al [40]), often such meta-meta information is not explicitly implemented but described as part of survey papers comparing different types of variability models [13,42]. Defining (generic) transformation operations for a particular set of variability modeling approaches then has to rely on such information.…”

Section: Transforming Variability Modelsmentioning

confidence: 99%

Towards Transforming Variability Models

Feichtinger

Rabiser

2020

Proceedings of the 24th ACM International Systems and Software Product Line Conference - Volume B

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A plethora of variability modeling approaches has been developed in the last 30 years, e.g., feature modeling, decision modeling, Orthogonal Variability Modeling (OVM), and UML-based variability modeling. While feature modeling approaches are probably the most common and well-known group of variability modeling approaches, even within that group multiple variants have been developed, i.e., there is not just one type of feature model. Many variability modeling approaches have been demonstrated as useful for a certain purpose, e.g., domain analysis or configuration of products derived from a software product line. Nevertheless, industry frequently develops their own custom solutions to manage variability. The (still growing) number of modeling approaches simply makes it difficult to find, understand, and eventually pick an approach for a specific (set of) systems or context. In this paper, we discuss usage scenarios, required capabilities and challenges for an approach for (semi-)automatically transforming variability models. Such an approach would support researchers and practitioners experimenting with and comparing different variability models and switching from one modeling approach to another. We present the key components of our envisioned approach and conclude with a research agenda. CCS CONCEPTS • Software and its engineering → Software product lines.

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Harmonized temporal feature modeling to uniformly perform, track, analyze, and replay software product line evolution

Cited by 16 publications

References 32 publications

Evolving System Families in Space and Time

Evolving System Families in Space and Time

Supporting feature-oriented evolution in industrial automation product lines

Towards Transforming Variability Models

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