Extracting the Source Code Context to Predict Import Changes using GPES

• Jaekwon Lee,
• Kisub Kim,
• Yong-Hyeon Lee,
• Jang-Eui Hong,
• Young-Hoon Seo,
• Byung-Do Yang,
• Woosung Jung,

Vol. 11, No. 2, February 27, 2017
10.3837/tiis.2017.02.035, Download Paper (Free):

• source code change
• context analysis
• library recommendation
• software repository
• extracting model

Abstract

One of the difficulties developers encounter in maintaining tasks of a large-scale software system is the updating of suitable libraries on time. Developers tend to miss or make mistakes when searching for and choosing libraries during the development process, or there may not be a stable library for the developers to use. We present a novel approach for helping developers modify software easily and on time and avoid software failures. Using a tool previously built by us called GPES, we collected information of projects, such as abstract syntax trees, tokens, software metrics, relations, and evolutions, for our experiments. We analyzed the contexts of source codes in existing projects to predict changes automatically and to recommend suitable libraries for the projects. The collected data show that researchers can reduce the overall cost of data analysis by transforming the extracted data into the required input formats with a simple query-based implementation. Also, we manually evaluated how the extracted contexts are similar to the description and we found that a sufficient number of the words in the contexts is similar and it might help developers grasp the domain of the source codes easily.

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