API method recommendation via explicit matching of functionality verb phrases

Due to the lexical gap between functionality descriptions and user queries, documentation-based API retrieval often produces poor results. Verb phrases and their phrase patterns are essential in both describing API functionalities and interpreting user queries. Thus we hypothesize that API retrieval...

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Main Authors: XIE, Wenkai, PENG, Xin, LIU, Mingwei, TREUDE, Christoph, XING, Zhenchang, ZHANG, Xiaoxin, ZHAO, Wenyun
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Language:English
Published: Institutional Knowledge at Singapore Management University 2020
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Online Access:https://ink.library.smu.edu.sg/sis_research/8892
https://ink.library.smu.edu.sg/context/sis_research/article/9895/viewcontent/fse20a.pdf
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spelling sg-smu-ink.sis_research-98952024-06-27T09:03:03Z API method recommendation via explicit matching of functionality verb phrases XIE, Wenkai PENG, Xin LIU, Mingwei TREUDE, Christoph XING, Zhenchang ZHANG, Xiaoxin ZHAO, Wenyun Due to the lexical gap between functionality descriptions and user queries, documentation-based API retrieval often produces poor results. Verb phrases and their phrase patterns are essential in both describing API functionalities and interpreting user queries. Thus we hypothesize that API retrieval can be facilitated by explicitly recognizing and matching between the fine-grained structures of functionality descriptions and user queries. To verify this hypothesis, we conducted a large-scale empirical study on the functionality descriptions of 14,733 JDK and Android API methods. We identified 356 different functionality verbs from the descriptions, which were grouped into 87 functionality categories, and we extracted 523 phrase patterns from the verb phrases of the descriptions. Building on these findings, we propose an API method recommendation approach based on explicit matching of functionality verb phrases in functionality descriptions and user queries, called PreMA. Our evaluation shows that PreMA can accurately recognize the functionality categories (92.8%) and phrase patterns (90.4%) of functionality description sentences; and when used for API retrieval tasks, PreMA can help participants complete their tasks more accurately and with fewer retries compared to a baseline approach. 2020-11-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/8892 info:doi/10.1145/3368089.3409731 https://ink.library.smu.edu.sg/context/sis_research/article/9895/viewcontent/fse20a.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 API Documentation API Retrieval Functionality Description Software Engineering
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic API Documentation
API Retrieval
Functionality Description
Software Engineering
spellingShingle API Documentation
API Retrieval
Functionality Description
Software Engineering
XIE, Wenkai
PENG, Xin
LIU, Mingwei
TREUDE, Christoph
XING, Zhenchang
ZHANG, Xiaoxin
ZHAO, Wenyun
API method recommendation via explicit matching of functionality verb phrases
description Due to the lexical gap between functionality descriptions and user queries, documentation-based API retrieval often produces poor results. Verb phrases and their phrase patterns are essential in both describing API functionalities and interpreting user queries. Thus we hypothesize that API retrieval can be facilitated by explicitly recognizing and matching between the fine-grained structures of functionality descriptions and user queries. To verify this hypothesis, we conducted a large-scale empirical study on the functionality descriptions of 14,733 JDK and Android API methods. We identified 356 different functionality verbs from the descriptions, which were grouped into 87 functionality categories, and we extracted 523 phrase patterns from the verb phrases of the descriptions. Building on these findings, we propose an API method recommendation approach based on explicit matching of functionality verb phrases in functionality descriptions and user queries, called PreMA. Our evaluation shows that PreMA can accurately recognize the functionality categories (92.8%) and phrase patterns (90.4%) of functionality description sentences; and when used for API retrieval tasks, PreMA can help participants complete their tasks more accurately and with fewer retries compared to a baseline approach.
format text
author XIE, Wenkai
PENG, Xin
LIU, Mingwei
TREUDE, Christoph
XING, Zhenchang
ZHANG, Xiaoxin
ZHAO, Wenyun
author_facet XIE, Wenkai
PENG, Xin
LIU, Mingwei
TREUDE, Christoph
XING, Zhenchang
ZHANG, Xiaoxin
ZHAO, Wenyun
author_sort XIE, Wenkai
title API method recommendation via explicit matching of functionality verb phrases
title_short API method recommendation via explicit matching of functionality verb phrases
title_full API method recommendation via explicit matching of functionality verb phrases
title_fullStr API method recommendation via explicit matching of functionality verb phrases
title_full_unstemmed API method recommendation via explicit matching of functionality verb phrases
title_sort api method recommendation via explicit matching of functionality verb phrases
publisher Institutional Knowledge at Singapore Management University
publishDate 2020
url https://ink.library.smu.edu.sg/sis_research/8892
https://ink.library.smu.edu.sg/context/sis_research/article/9895/viewcontent/fse20a.pdf
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