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Article

Automatic parameter recommendation for practical API usage

Authors:

Peizhao OuAuthors Info & Claims

ICSE '12: Proceedings of the 34th International Conference on Software Engineering

Pages 826 - 836

Published: 02 June 2012 Publication History

Abstract

Programmers extensively use application programming interfaces (APIs) to leverage existing libraries and frameworks. However, correctly and efficiently choosing and using APIs from unfamiliar libraries and frameworks is still a non-trivial task. Programmers often need to ruminate on API documentations (that are often incomplete) or inspect code examples (that are often absent) to learn API usage patterns. Recently, various techniques have been proposed to alleviate this problem by creating API summarizations, mining code examples, or showing common API call sequences. However, few techniques focus on recommending API parameters.

In this paper, we propose an automated technique, called Precise, to address this problem. Differing from common code completion systems, Precise mines existing code bases, uses an abstract usage instance representation for each API usage example, and then builds a parameter usage database. Upon a request, Precise queries the database for abstract usage instances in similar contexts and generates parameter candidates by concretizing the instances adaptively.

The experimental results show that our technique is more general and applicable than existing code completion systems, specially, 64% of the parameter recommendations are useful and 53% of the recommendations are exactly the same as the actual parameters needed. We have also performed a user study to show our technique is useful in practice.

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Cited By

Wang YLiu HGao STang X(2023)Animation2API: API Recommendation for the Implementation of Android UI AnimationsIEEE Transactions on Software Engineering10.1109/TSE.2023.329497149:9(4411-4428)Online publication date: 11-Aug-2023
https://dl.acm.org/doi/10.1109/TSE.2023.3294971
Dilhara MKetkar ADig D(2021)Understanding Software-2.0ACM Transactions on Software Engineering and Methodology10.1145/345347830:4(1-42)Online publication date: 23-Jul-2021
https://dl.acm.org/doi/10.1145/3453478
Thayer KChasins SKo A(2021)A Theory of Robust API KnowledgeACM Transactions on Computing Education10.1145/344494521:1(1-32)Online publication date: 28-Jan-2021
https://dl.acm.org/doi/10.1145/3444945
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Information & Contributors

Information

Published In

cover image ACM Conferences

ICSE '12: Proceedings of the 34th International Conference on Software Engineering

June 2012

1657 pages

ISBN:9781467310673

General Chair:
Martin Glinz,
Program Chairs:
Gail Murphy,
Mauro Pezzè

Sponsors

SIGSOFT: ACM Special Interest Group on Software Engineering

Publisher

IEEE Press

Publication History

Published: 02 June 2012

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Conference

ICSE '12

Sponsor:

SIGSOFT

ICSE '12: 34th International Conference on Software Engineering

June 2 - 9, 2012

Zurich, Switzerland

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Overall Acceptance Rate 276 of 1,856 submissions, 15%

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Cited By

Wang YLiu HGao STang X(2023)Animation2API: API Recommendation for the Implementation of Android UI AnimationsIEEE Transactions on Software Engineering10.1109/TSE.2023.329497149:9(4411-4428)Online publication date: 11-Aug-2023
https://dl.acm.org/doi/10.1109/TSE.2023.3294971
Dilhara MKetkar ADig D(2021)Understanding Software-2.0ACM Transactions on Software Engineering and Methodology10.1145/345347830:4(1-42)Online publication date: 23-Jul-2021
https://dl.acm.org/doi/10.1145/3453478
Thayer KChasins SKo A(2021)A Theory of Robust API KnowledgeACM Transactions on Computing Education10.1145/344494521:1(1-32)Online publication date: 28-Jan-2021
https://dl.acm.org/doi/10.1145/3444945
Szalay RSinkovics ÁPorkoláb Z(2021)Practical heuristics to improve precision for erroneous function argument swapping detection in C and C++Journal of Systems and Software10.1016/j.jss.2021.111048181:COnline publication date: 1-Nov-2021
https://dl.acm.org/doi/10.1016/j.jss.2021.111048
Raelijohn EFamelis MSahraoui HGnesi SPlat NDay NRossi M(2019)A vision for helping developers use APIs by leveraging temporal patternsProceedings of the 7th International Workshop on Formal Methods in Software Engineering10.1109/FormaliSE.2019.00019(95-98)Online publication date: 27-May-2019
https://dl.acm.org/doi/10.1109/FormaliSE.2019.00019
Nguyen SNguyen TLi YWang SZimmermann TLawall JMarinov D(2019)Combining program analysis and statistical language model for code statement completionProceedings of the 34th IEEE/ACM International Conference on Automated Software Engineering10.1109/ASE.2019.00072(710-721)Online publication date: 10-Nov-2019
https://dl.acm.org/doi/10.1109/ASE.2019.00072
Lamothe MShang WZaidman AKamei YHill E(2018)Exploring the use of automated API migrating techniques in practiceProceedings of the 15th International Conference on Mining Software Repositories10.1145/3196398.3196420(503-514)Online publication date: 28-May-2018
https://dl.acm.org/doi/10.1145/3196398.3196420
Dotzler GKamp MKreutzer PPhilippsen MBodden ESchäfer WDeursen AZisman A(2017)More accurate recommendations for method-level changesProceedings of the 2017 11th Joint Meeting on Foundations of Software Engineering10.1145/3106237.3106276(798-808)Online publication date: 21-Aug-2017
https://dl.acm.org/doi/10.1145/3106237.3106276
Ichinco MHnin WKelleher CMark GFussell SLampe Cschraefel mHourcade JAppert CWigdor D(2017)Suggesting API Usage to Novice Programmers with the Example GuruProceedings of the 2017 CHI Conference on Human Factors in Computing Systems10.1145/3025453.3025827(1105-1117)Online publication date: 2-May-2017
https://dl.acm.org/doi/10.1145/3025453.3025827
Mondal MRoy CSchneider KMindel MMüller HOnut V(2016)An exploratory study on change suggestions for methods using clone detectionProceedings of the 26th Annual International Conference on Computer Science and Software Engineering10.5555/3049877.3049886(85-95)Online publication date: 31-Oct-2016
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