Summarizing source code with transferred API knowledge

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...

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Main Authors: HU, Xing, LI, Ge, XIA, Xin, LO, David, LU, Shuai, JIN, Zhi
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Language:English
Published: Institutional Knowledge at Singapore Management University 2018
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Online Access:https://ink.library.smu.edu.sg/sis_research/4295
https://ink.library.smu.edu.sg/context/sis_research/article/5298/viewcontent/Ijcai_2018_314_pvoa.pdf
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Institution: Singapore Management University
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spelling sg-smu-ink.sis_research-52982025-02-11T01:25:44Z Summarizing source code with transferred API knowledge HU, Xing LI, Ge XIA, Xin LO, David LU, Shuai JIN, Zhi 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. 2018-07-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/4295 info:doi/10.24963/ijcai.2018/314 https://ink.library.smu.edu.sg/context/sis_research/article/5298/viewcontent/Ijcai_2018_314_pvoa.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Software Engineering
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Software Engineering
spellingShingle Software Engineering
HU, Xing
LI, Ge
XIA, Xin
LO, David
LU, Shuai
JIN, Zhi
Summarizing source code with transferred API knowledge
description 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.
format text
author HU, Xing
LI, Ge
XIA, Xin
LO, David
LU, Shuai
JIN, Zhi
author_facet HU, Xing
LI, Ge
XIA, Xin
LO, David
LU, Shuai
JIN, Zhi
author_sort HU, Xing
title Summarizing source code with transferred API knowledge
title_short Summarizing source code with transferred API knowledge
title_full Summarizing source code with transferred API knowledge
title_fullStr Summarizing source code with transferred API knowledge
title_full_unstemmed Summarizing source code with transferred API knowledge
title_sort summarizing source code with transferred api knowledge
publisher Institutional Knowledge at Singapore Management University
publishDate 2018
url https://ink.library.smu.edu.sg/sis_research/4295
https://ink.library.smu.edu.sg/context/sis_research/article/5298/viewcontent/Ijcai_2018_314_pvoa.pdf
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