Mining Software Repositories for Automatic Interface Recommendation

Abstract

There are a large number of open source projects in software repositories for developers to reuse. During software development and maintenance, developers can leverage good interfaces in these open source projects and establish the framework of the new project quickly when reusing interfaces in these open source projects. However, if developers want to reuse them, they need to read a lot of code files and learn which interfaces can be reused. To help developers better take advantage of the available interfaces used in software repositories, we previously proposed an approach to automatically recommend interfaces by mining existing open source projects in the software repositories. We mainly used the LDA (Latent Dirichlet Allocation) topic model to construct the Feature-Interface Graph for each software project and recommended the interfaces based on the Feature-Interface Graph. In this paper, we improve our previous approach by clustering the recommending interfaces on the Feature-Interface Graph, which can recommend more accurate interfaces for developers to reuse. We evaluate the effectiveness of the improved approach and the results show that the improved approach can be more efficient to recommend more accurate interfaces for reuse over our previous work.