Achieving Feature Location in Families of Models Through the Use of Search-Based Software Engineering

作者：Font Jaime; Arcega Lorena; Haugen Oystein; Cetina Carlos

来源：IEEE Transactions on Evolutionary Computation, 2018, 22(3): 363-377.

DOI：10.1109/TEVC.2017.2751100

• Evolutionary algorithm (EA)
• families of models
• feature location (FL)
• search-based software engineering (SBSE)

The application of search-based software engineering techniques to new problems is increasing. Feature location is one of the most important and common activities performed by developers during software maintenance and evolution. Features must be located across families of products and the software artifacts that realize each feature must be identified. However, when dealing with industrial software artifacts, the search space can be huge. We propose and compare five search algorithms to locate features over families of product models guided by latent semantic analysis (LSA), a technique that measures similarities between textual queries. The algorithms are applied to two case studies from our industrial partners (leading manufacturers of home appliances and rolling stock) and are compared in terms of precision and recall. Statistical analysis of the results is performed to provide evidence of the significance of the results. The combination of an evolutionary algorithm with LSA can be used to locate features in families of models from industrial scenarios such as the ones from our industrial partners.

• 出版日期2018-8