Software product lines and variability modeling: A tertiary study

Raatikainen, Mikko; Tiihonen, Juha; Männistö, Tomi

doi:10.1016/j.jss.2018.12.027

Cited by 85 publications

(36 citation statements)

References 24 publications

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“…These general characteristics are found in most of the existing approaches [3,11,16,21,32,36] and are a good basis to define transformation operations.…”

Section: Transforming Variability Modelsmentioning

confidence: 99%

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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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“…These general characteristics are found in most of the existing approaches [3,11,16,21,32,36] and are a good basis to define transformation operations.…”

Section: Transforming Variability Modelsmentioning

confidence: 99%

“…It is core to software product line engineering methodologies [31]. Several works have focused on comparing existing variability modeling approaches, languages, and tools [3,5,8,11,21,32,36]. The ESPLA catalogue [30] provides pointers to numerous case studies, using diverse types of variability models.…”

Section: Introductionmentioning

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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“…There is a large number of SLRs, mapping studies, and surveys that investigate Variability Modeling (VM) approaches [3,5,9,10,12,34]. Raatikainen et al [34] report in their tertiary study on SLRs in the area of Software Product Lines (SPLs) low representation of research on the variability of process models and quality attributes. They suggest to adapt and combine VM approaches and apply them to specific industry problems.…”

Section: Variability Modelingmentioning

confidence: 99%

Integrating Variability Modeling of Products, Processes, and Resources in Cyber-Physical Production Systems Engineering

Meixner

2020

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

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The Industry 4.0 initiative envisions the flexible and optimized production of customized products on Cyber-Physical Production Systems (CPPSs) that consist of subsystems coordinated to conduct complex production processes. Hence, accurate CPPS modeling requires integrating the modeling of variability for Product-Process-Resource (PPR) aspects. Yet, current variability modeling approaches treat structural and behavioral variability separately, leading to inaccurate CPPS production models that impede CPPS engineering and optimization. This paper proposes a PhD project for integrated variability modeling of PPR aspects to improve the accuracy of production models with variability for CPPS engineers and production optimizers. The research project follows the Design Science approach aiming for the iterative design and evaluation of (a) a framework to categorize currently incomplete and scattered models and methods for PPR variability modeling as a foundation for an integrated model; and (b) a modeling approach for more accurate integrated PPR variability modeling. The planned research will provide the Software Product Line (SPL) and CPPS engineering research communities with (a) novel models, methods, and insights on integrated PPR variability modeling, (b) open data from CPPS engineering use cases for common modeling, and (c) empirical data from field studies for shared analysis and evaluation. CCS CONCEPTS • Software and its engineering → Software product lines.

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“…Variability modeling is the discipline of explicitly representing variability in dedicated models that describe the common and variable aspects of a set of (software) systems [9] as the basis for Software Product Line (SPL) engineering [32]. Several works have focused on comparing existing variability modeling approaches, tools, and languages [4,7,12,19,33,39] and on analyzing their use in industry [9]. Still, there is currently no unified or standardized variability modeling approach available.…”

Section: Introductionmentioning

confidence: 99%

Variability Transformation from Industrial Engineering Artifacts

Feichtinger

Meixner

Rabiser

et al. 2020

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

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Many variability modeling approaches have been proposed to explicitly represent the commonalities and variability in (software) product lines. Unfortunately, practitioners in industry still develop custom solutions to manage variability of various artifacts, like requirements documents or design spreadsheets. These customdeveloped variability representations often miss important variability information, e.g., information required to assemble production goods. In this paper, we introduce the Variability Evolution Roundtrip Transformation (VERT) process. The process enables practitioners from the Cyber-Physical Production Systems domain to transform custom-developed engineering variability artifacts to a feature model, evolve and optimize the model, and transform it back to the original engineering artifacts. We build on an existing transformation approach for variability models and show the feasibility of the process using a real-world use case from an industry partner. We report on an initial feasibility study conducted with our industry partners' domain experts and on lessons learned regarding variability transformation of engineering variability artifacts. CCS CONCEPTS • Software and its engineering → Software product lines.

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Software product lines and variability modeling: A tertiary study

Cited by 85 publications

References 24 publications

Towards Transforming Variability Models

Towards Transforming Variability Models

Integrating Variability Modeling of Products, Processes, and Resources in Cyber-Physical Production Systems Engineering

Variability Transformation from Industrial Engineering Artifacts

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