Towards a Flexible Approach for Variability Mining

Software Product Line (SPL) Engineering relies on explicitly documenting and managing variability information, typically in variability models such as feature models, and relating them with reusable artifacts, e.g., software components. Many companies still rely on clone-and-own reuse approaches and could benefit from adopting an SPL approach instead. However, extracting variability information from existing systems is often challenging due to their size and complexity. Also, manually creating and maintaining variability models and relating them with reusable artifacts is very expensive and requires expert knowledge. To address this problem, SPL reverse-engineering approaches try to automatically extract variability information from existing systems to populate variability models with it. Unfortunately, many existing approaches are limited to a single artifact type and only a few more widely applicable methods have been proposed. In this short paper, we present our vision of a flexible, extensible and artifact-independent approach, which provides a framework for users to mine the variability of their existing system variants and automatically reverse-engineer SPLs. We discuss challenges and give an overview of a possible architecture as well as the steps necessary to realize our approach.

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Publication Details

Published
2024-08-12
DOI
https://doi.org/10.1145/3646548.3676543
Citations
1
Primary Topic
Software Engineering Research
Type
article
Field-Weighted Citation Impact
0.78
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article

Towards a Flexible Approach for Variability Mining

Rick Rabiser, Alexander Stummer, Anna-Lena Hager
1 citations
Software Engineering Research
0.78
article

Towards a Flexible Approach for Variability Mining

Rick Rabiser, Alexander Stummer, Anna-Lena Hager
article en
1 citations

Abstract

Software Product Line (SPL) Engineering relies on explicitly documenting and managing variability information, typically in variability models such as feature models, and relating them with reusable artifacts, e.g., software components. Many companies still rely on clone-and-own reuse approaches and could benefit from adopting an SPL approach instead. However, extracting variability information from existing systems is often challenging due to their size and complexity. Also, manually creating and maintaining variability models and relating them with reusable artifacts is very expensive and requires expert knowledge. To address this problem, SPL reverse-engineering approaches try to automatically extract variability information from existing systems to populate variability models with it. Unfortunately, many existing approaches are limited to a single artifact type and only a few more widely applicable methods have been proposed. In this short paper, we present our vision of a flexible, extensible and artifact-independent approach, which provides a framework for users to mine the variability of their existing system variants and automatically reverse-engineer SPLs. We discuss challenges and give an overview of a possible architecture as well as the steps necessary to realize our approach.

Johannes Kepler University of Linz (AT)
Openalex Percentile: Top 22%
Software Engineering Research
0.78
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