Towards a Conceptual Model for Unifying Variability in Space and Time

Ananieva, Sofia; Kehrer, Timo; Klare, Heiko; Koziolek, Anne; Lönn, Henrik; Ramesh, S.; Burger, Andreas; Taentzer, Gabriele; Westfechtel, Bernhard

doi:10.1145/3307630.3342412

Cited by 12 publications

(6 citation statements)

References 21 publications

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“…We refer to the resulting model as Fig. 2 The initial conceptual model for unifying concepts of variability in space (green) and in time (orange) with common concepts (white) (Ananieva et al 2019b) initial conceptual model (Ananieva et al 2019b). Based on interviews with tool developers and discussions during follow-up workshops, we refined the initial conceptual model by relying on the knowledge of experts in the area of managing both variability dimensions simultaneously (Ananieva et al 2020).…”

Section: Initial Conceptual Modelmentioning

confidence: 99%

“…Modern software systems exist in many variations to fulfill, for instance, different customer requirements, hardware limitations, and regulations (Apel et al 2013;Pohl et al 2005;Estublier 2000;Stȃnciulescu et al 2015). Each variation may be distinguished based on which dimension it stems from Conradi and Westfechtel (1998), Ananieva et al (2019b), and Strüber et al (2019). First, variations can be implemented as feature options in a system.…”

Section: Introductionmentioning

confidence: 99%

“…As a consequence, it helps to proactively avoid many of the problems tackled in research on variability evolution and mining (e.g., the mining of feature evolution from source code repositories (Dintzner et al 2016;Kröher et al 2018)). In our previous work (Ananieva et al 2019b;Ananieva et al 2020), we described how we constructed a conceptual model relating the concepts of SPLE and SCM to provide a unified foundation of both areas, while also introducing hybrid concepts that emerge from the combination of variability in space and time. To derive the conceptual model, we systematically elicited concepts of 10 tools (cf.…”

Section: Introductionmentioning

confidence: 99%

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

Scholch

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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: Initial Conceptual Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

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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“…In an open-source model, collaborative feature modeling tools will be needed to allow multiple users to contribute their domain knowledge and refine the models over time. As such some recent work has emerged to formalize evolutionary operations on SPLs and their feature models (Mitschke and Eichberg 2008;Nieke et al 2016;Ananieva et al 2019;Hinterreiter et al 2019). For example temporal feature models (Hinterreiter et al 2019;Nieke et al 2016) develop a firstclass notation for evolution in a feature model.…”

Section: Importance Of Tools Supporting Spl Evolutionmentioning

confidence: 99%

An empirical investigation of organic software product lines

et al. 2021

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Software product line engineering is a best practice for managing reuse in families of software systems that is increasingly being applied to novel and emerging domains. In this work we investigate the use of software product line engineering in one of these new domains, synthetic biology. In synthetic biology living organisms are programmed to perform new functions or improve existing functions. These programs are designed and constructed using small building blocks made out of DNA. We conjecture that there are families of products that consist of common and variable DNA parts, and we can leverage product line engineering to help synthetic biologists build, evolve, and reuse DNA parts. In this paper we perform an investigation of domain engineering that leverages an open-source repository of more than 45,000 reusable DNA parts. We show the feasibility of these new types of product line models by identifying features and related artifacts in up to 93.5% of products, and that there is indeed both commonality and variability. We then construct feature models for four commonly engineered functions leading to product lines ranging from 10 to 7.5 × 1020 products. In a case study we demonstrate how we can use the feature models to help guide new experimentation in aspects of application engineering. Finally, in an empirical study we demonstrate the effectiveness and efficiency of automated reverse engineering on both complete and incomplete sets of products. In the process of these studies, we highlight key challenges and uncovered limitations of existing SPL techniques and tools which provide a roadmap for making SPL engineering applicable to new and emerging domains.

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“…A range of tools tackles selected areas of SPL evolution, e.g., DeltaEcore [62], ECCO [14], SuperMod [57,58], VaVe [4], SiPL [49], EvoFM [10,11], EvoPL [9,55] or DarwinSPL [41]. Recently, there have also been first attempts to harmonize modeling of SPL evolution by integrating [17] or abstracting from [3] various of the different underlying notations. Even though the need and principle feasibility for SPL evolution planning has been recognized before [9,48], the vast majority of existing concepts and tools does not tackle this challenge.…”

Section: Related Workmentioning

confidence: 99%

Consistency-preserving evolution planning on feature models

Hoff

Nieke

Seidl

et al. 2020

Proceedings of the 24th ACM Conference on Systems and Software Product Line: Volume a - Volume A

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A software product line (SPL) enables large-scale reuse in a family of related software systems through configurable features. SPLs represent a long-term investment so that their ongoing evolution becomes paramount and requires careful planning. While existing approaches enable to create an evolution plan for an SPL on feature-model (FM) level, they assume the plan to be rigid and do not support retroactive changes. In this paper, we present a method that enables to create and retroactively adapt an FM evolution plan while preventing undesired impacts on its structural and logical consistency. This method is founded in structural operational semantics and linear temporal logic. We implement our method using rewriting logic, integrate it within an FM tool suite and perform an evaluation using a collection of existing FM evolution scenarios. CCS CONCEPTS• Software and its engineering → Software product lines; Software evolution; Software notations and tools.

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Towards a Conceptual Model for Unifying Variability in Space and Time

Cited by 12 publications

References 21 publications

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

An empirical investigation of organic software product lines

Consistency-preserving evolution planning on feature models

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