Second International Workshop on Variability and Evolution of Software-Intensive Systems (VariVolution 2019)

Krüger, Jacob; Ananieva, Sofia; Gerling, Lea; Walkingshaw, Eric

doi:10.1145/3336294.3342367

Cited by 7 publications

(2 citation statements)

References 1 publication

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“…Simply combining existing approaches for managing both variability dimensions does also not suffice, since developers need to deal with a heterogeneous tool landscape (e.g., a VCS; potentially multiple variability mechanisms, such as a preprocessor and a build system as in the Linux kernel; and variability mining tools)-which hampers cross-dimensional variability modeling and analyses, for instance, for capturing the volatility (i.e., frequency of change) of a feature. The combination of SPLE and SCM, and thus explicit proactive management of variability in space and time during a system's development, aims at solving these problems and has only recently received increasing attention (Berger et al 2019;Linsbauer et al 2018;Nieke et al 2019;Strüber et al 2019;Thüm et al 2019;Kehrer et al 2021).…”

Section: Introductionmentioning

confidence: 99%

Towards Automatic Parsing of Structured Visual Content through the Use of Synthetic Data

Scholch

Steinhauser

Beichter

et al. 2022

2022 26th International Conference on Pattern Recognition (ICPR)

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With the increasing demand for customized systems and rapidly evolving technology, software engineering faces many challenges. A particular challenge is the development and maintenance of systems that are highly variable both in space (concurrent variations of the system at one point in time) and time (sequential variations of the system, due to its evolution). Recent research aims to address this challenge by managing variability in space and time simultaneously. However, this research originates from two different areas, software product line engineering and software configuration management, resulting in nonuniform terminologies and a varying understanding of concepts. These problems hamper the communication and understanding of involved concepts, as well as the development of techniques that unify variability in space and time. To tackle these problems, we performed an iterative, expert-driven analysis of existing tools from both research areas to derive a conceptual model that integrates and unifies concepts of both dimensions of variability. In this article, we first explain the construction process and present the resulting conceptual model. We validate the model and discuss its coverage and granularity with respect to established concepts of variability in space and time. Furthermore, we perform a formal concept analysis to discuss the commonalities and differences among the tools we considered. Finally, we show illustrative applications to explain how the conceptual model can be used in practice to derive conforming tools. The conceptual model unifies concepts and relations used in software product line engineering and software configuration management, provides a unified terminology and common ground for researchers and developers for comparing their works, clarifies communication, and prevents redundant developments.

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Section: Introductionmentioning

confidence: 99%

Towards Automatic Parsing of Structured Visual Content through the Use of Synthetic Data

Scholch

Steinhauser

Beichter

et al. 2022

2022 26th International Conference on Pattern Recognition (ICPR)

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“…Variability in time refers to evolutionary changes of a system, such as bug fixes or optimizations, and is the focus of software configuration management (SCM) [14] and version-control systems (VCSs) [50]. Dealing with both dimensions of variability is essential for maintaining long-living systems [8,26,32,41,55,58], such as automotive systems. While some variation control systems (VarCSs) attempt to manage both variability dimensions, their behavior varies widely [33].…”

Section: Introductionmentioning

confidence: 99%

Unified Operations for Variability in Space and Time

Ananieva

Greiner

Krueger

et al. 2022

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

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Software and systems engineering is challenged by variability in space (concurrent variations at a single point in time) and time (sequential variations due to evolution). Managing both dimensions of variability independently is cumbersome and error-prone. A common foundation for operations on these dimensions is still missing, hampering the comparison and integration of existing techniques coping with variability in space and time as well as the design of new ones. In this paper, we address this problem by systematically identifying, categorizing, and unifying operations from contemporary tools and extending them to cope with both variability dimensions. Based on our gained insights, we identify gaps and trade-offs in current tools for managing variability in space and time, and discuss open challenges. The unified operations establish a common foundation that helps researchers and practitioners to gain a deeper understanding of existing techniques and tools for managing variability in space and/or time, analyze and compare them, and design new ones. CCS CONCEPTS• Software and its engineering → Software version control; Software product lines; Software configuration management and version control systems.

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A conceptual model for unifying variability in space and time: Rationale, validation, and illustrative applications

et al. 2022

View full text Add to dashboard Cite

With the increasing demand for customized systems and rapidly evolving technology, software engineering faces many challenges. A particular challenge is the development and maintenance of systems that are highly variable both in space (concurrent variations of the system at one point in time) and time (sequential variations of the system, due to its evolution). Recent research aims to address this challenge by managing variability in space and time simultaneously. However, this research originates from two different areas, software product line engineering and software configuration management, resulting in non-uniform terminologies and a varying understanding of concepts. These problems hamper the communication and understanding of involved concepts, as well as the development of techniques that unify variability in space and time. To tackle these problems, we performed an iterative, expert-driven analysis of existing tools from both research areas to derive a conceptual model that integrates and unifies concepts of both dimensions of variability. In this article, we first explain the construction process and present the resulting conceptual model. We validate the model and discuss its coverage and granularity with respect to established concepts of variability in space and time. Furthermore, we perform a formal concept analysis to discuss the commonalities and differences among the tools we considered. Finally, we show illustrative applications to explain how the conceptual model can be used in practice to derive conforming tools. The conceptual model unifies concepts and relations used in software product line engineering and software configuration management, provides a unified terminology and common ground for researchers and developers for comparing their works, clarifies communication, and prevents redundant developments.

show abstract

Second International Workshop on Variability and Evolution of Software-Intensive Systems (VariVolution 2019)

Cited by 7 publications

References 1 publication

Towards Automatic Parsing of Structured Visual Content through the Use of Synthetic Data

Towards Automatic Parsing of Structured Visual Content through the Use of Synthetic Data

Unified Operations for Variability in Space and Time

A conceptual model for unifying variability in space and time: Rationale, validation, and illustrative applications

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