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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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 |
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Software Engineering HU, Xing LI, Ge XIA, Xin LO, David LU, Shuai JIN, Zhi Summarizing source code with transferred API knowledge |
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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. |
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HU, Xing LI, Ge XIA, Xin LO, David LU, Shuai JIN, Zhi |
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HU, Xing LI, Ge XIA, Xin LO, David LU, Shuai JIN, Zhi |
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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 |
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Summarizing source code with transferred API knowledge |
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Summarizing source code with transferred API knowledge |
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summarizing source code with transferred api knowledge |
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Institutional Knowledge at Singapore Management University |
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2018 |
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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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