No abstract

Software product line supports structured reuse of software artifacts in order to realize the maintenance and evolution of the typically large number of variants, which promotes the industrialization of software development, especially for software-intensive products. However, for a legacy system, it is non-trivial to gain information about commonalities and differences of the variants. Meanwhile, software requirements specifications as the initial artifacts can be used to achieve this information to generate a domain model. Unfortunately, manually analyzing these requirements is time-consuming and inefficient. To address this problem, we explored the usage of feature extraction techniques to automatically extract domain knowledge from requirements to assist domain engineers. In detail, we applied Doc2Vec and a clustering algorithm to process the requirements for achieving the initial feature tree. Moreover, we utilized key words/phrases extraction techniques to provide key information to domain engineers for further analyzing the extraction results. In particular, we developed a GUI to support the extraction process. The empirical evaluation indicates that most of the extracted features and terms are beneficial to improve the process of feature extraction. CCS CONCEPTS • Computing methodologies → Natural language processing; • Software and its engineering → Software product lines.