HESA: The Construction and Evaluation of Hierarchical Software Feature Repository

Nowadays, the demand for software resources on different granularity is becoming prominent in software engineering field. However, a large quantity of heterogeneous software resources have not been organized in a reasonable and efficient way. Software features, a kind of important knowledge for software reuse, are ideal materials to characterize software resources. Our preliminary study shows that the effectiveness of feature-related tasks, such as software resource retrieval and feature location, will be greatly improved, if a multi-grained feature repository is available. In this paper, we construct a Hierarchical rEpository of Software feAture (HESA), in which a novel hierarchical clustering approach is proposed. For a given domain, we first aggregate a large number of feature descriptions from multiple online software repositories. Then we cluster these descriptions into a flexible hierarchy by mining their hidden semantic structures. Finally, we implement an online search engine on HESA and conduct a user study to evaluate our approach quantitatively. The results show that HESA can organize software features in a more reasonable way compared to the classic and the state-of-the-art approaches. Keywords—Software reuse; Mining Software repository; Feature-ontology; Clustering;