Database semantics recovery through analysis of dynamic SQL statements
Journal on data semantics XV
An overview of techniques for detecting software variability concepts in source code
ER'11 Proceedings of the 30th international conference on Advances in conceptual modeling: recent developments and new directions
Improving feature location using structural similarity and iterative graph mapping
Journal of Systems and Software
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Feature models are widely employed in domain specific software development to specify the domain requirements with commonality and variability. A feature model is usually constructed by domain experts after comprehensive domain analysis. In this paper, we propose a method to recover an initial domain feature model from multiple existing domain applications using data access semantics and formal concept analysis (FCA). In the method, we first establish mappings among the database schemas of all the reference implementations. Then, we capture the data access semantics of each method in each reference implementation. Based on the pre-established data mapping, we can mix methods from different applications together and conduct formal concept analysis with the data access semantics as intention. After that,further concept merging/pruning and variability analysis are performed to produce the domain feature model. In order to evaluate the effectiveness of our method, we conduct a case study on three open-source forum applications and present comprehensive analysis and discussions on the results.