Abstract
Software Product Lines (SPLs) enable the derivation of a family of products based on variability management techniques. Inspired by the manufacturing industry, SPLs use feature configurations to satisfy different customer needs, along with reusable assets associated to the features, to allow systematic and planned reuse. SPLs are reported to have numerous benefits such as time-to-market reduction, productivity increase or product quality improvement.However, the barriers to adopt an SPL are equally numerous requiring a high up-front investment in domain analysis and implementation. In this context, to create variants, companies more commonly rely on ad-hoc reuse techniques such as copy-paste-modify.
Capitalizing on existing variants by extracting the common and varying elements is referred to as extractive approaches for SPL adoption. Extractive SPL adoption allows the migration from single-system development mentality to SPL practices. Several activities are involved to achieve this goal. Due to the complexity of artefact variants, feature identification is needed
to analyse the domain variability. Also, to identify the associated implementation elements of the features, their location is needed as well. In addition, feature constraints should be identified to guarantee that customers are not able to select invalid feature combinations (e.g., one feature requires or excludes another). Then, the reusable assets associated to the feature
should be constructed. And finally, to facilitate the communication among stakeholders, a comprehensive feature model need to be synthesized. While several approaches have been proposed for the above-mentioned activities, extractive SPL adoption remains challenging.
A recurring barrier consists in the limitation of existing techniques to be used beyond the specific types of artefacts that they initially targeted, requiring inputs and providing outputs at different granularity levels and with different representations. Seamlessly address the activities within the same environment is a challenge by itself.
This dissertation presents a unified, generic and extensible framework for mining software artefact variants in the context of extractive SPL adoption. We describe both its principles and its realization in Bottom-Up Technologies for Reuse (BUT4Reuse). Special attention is paid to model-driven development scenarios. A unified process and representation would enable practitioners and researchers to empirically analyse and compare different techniques.
Therefore, we also focus on benchmarks and in the analysis of variants, in particular, in benchmarking feature location techniques and in identifying families of variants in the wild for experimenting with feature identification techniques. We also present visualisation paradigms to support domain experts on feature naming during feature identification and to support on
feature constraints discovery. Finally, we investigate and discuss the mining of artefact variants for SPL analysis once the SPL is already operational. Concretely, we present an approach to find relevant variants within the SPL configuration space guided by end user assessments.
| Date of Award | 2016 |
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| Original language | English |
| Awarding Institution |
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