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.
Highlights
Interfaces are an integral part of software projects, which is an important means for software design
After constructing the Feature-Interface Graph (FIG) for each of the relevant projects, we can obtain the information about the topics of the software and their interfaces and the number of each interface being invoked in the software
We have conducted some empirical studies to show which number of topics is good for interface recommendation, and the results show that four number of topics is a relatively good choice
Summary
Interfaces are an integral part of software projects, which is an important means for software design. We proposed an approach to effectively mine the software repositories for automatic interface recommendation [16]. We use the LDA topic model to extract the topics of open source projects in the open source software repositories and identify the relevant open source projects. In this way, we do not need to construct the FIGs for each project in the software repositories, which is costly. (i) We improve our previous work and propose a more effective approach for automatic interface recommendation by mining software repositories.
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