"Summarizing source code with transferred API knowledge" by Xing HU, Ge LI et al.
 

Publication Type

Conference Proceeding Article

Version

publishedVersion

Publication Date

7-2018

Abstract

Code summarization, aiming to generate succinct natural language description of source code, is extremely useful for code search and code comprehension. It has played an important role in software maintenance and evolution. Previous approaches generate summaries by retrieving summaries from similar code snippets. However, these approaches heavily rely on whether similar code snippets can be retrieved, how similar the snippets are, and fail to capture the API knowledge in the source code, which carries vital information about the functionality of the source code. In this paper, we propose a novel approach, named TL-CodeSum, which successfully uses API knowledge learned in a different but related task to code summarization. Experiments on large-scale real-world industry Java projects indicate that our approach is effective and outperforms the state-of-the-art in code summarization.

Discipline

Software Engineering

Research Areas

Software and Cyber-Physical Systems

Publication

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence (IJCAI 2018), Stockholm, Sweden, July 13-19

First Page

2269

Last Page

2275

Identifier

10.24963/ijcai.2018/314

Publisher

IJCAI

City or Country

Stockholm, Sweden

Additional URL

https://doi.org/10.24963/ijcai.2018/314

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