Abstract
In industrial practice the clone-and-own strategy is often applied when in the pressure of high demand of customized features. The adoption of software product line (SPL) architecture is a large one time investment that affects both technical and organizational issues. The analysis of the feature structure is a crucial point in the SPL adoption process involving domain experts working at a higher level of abstraction and developers working directly on the program code. We propose automatic methods to extract feature-to-program links starting from very high level set of features provided by domain experts. For this purpose we combine call graph information with textual similarity between code and high level features. In addition, in depth understanding of the feature structure is supported by finding communities between programs and relating them to features. As features are originated from domain experts, community analysis reveals discrepancies between expert view and internal code structure. We found that communities correspond well to the high level features, with usually more than half of feature code located in specialized communities. We report experiments at two levels of features and more than 2000 Magic 4GL programs in an industrial SPL adoption project.
Highlights
Maintaining parallel versions of a software satisfying various customer needs is challenging
IR represents the result set of the information retrieval technique, CG represents the pairs attained by call graph, while ESS represents the set of programs considered most essential, detected by both techniques
During our experiments we considered the following community detection algorithms provided by the R software environment: Edge Betweenness: Edge betweenness scores are the number of shortest paths that pass through an edge
Summary
Maintaining parallel versions of a software satisfying various customer needs is challenging. As the number of product variants increases, a more viable solution is needed through systematic code level reuse. A natural step towards more effective development is the adoption of product line architecture (Clements and Northrop, 2001). Product line adoption is usually approached from three directions: the proactive approach starts with domain analysis and applies variability management from scratch. The reactive approach incrementally replies to the new customer needs when they arise. When there are already a number of systems in production, the extractive approach seems to be the most feasible choice. During the extractive approach the adoption process benefits from systematic reuse of existing design and architectural knowledge (Krueger, 2002). An advantage of the extractive approach in general is that several reverse engineering methods exist to support feature extraction and analysis (Kästner et al, 2014; Assunção and Vergilio, 2014; Eyal-Salman et al, 2012)
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