NBSL: a supervised classification model of pull request in GitHub

Song Yu; Li Xu; Yan Zhang; Jinsong Wu; Zhifang Liao; Yanbing Li

doi:10.1109/ICC.2018.8422103

NBSL: a supervised classification model of pull request in GitHub

Song Yu, Li Xu, Yan Zhang, Jinsong Wu, Zhifang Liao^*, Yanbing Li

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

14 Citations (Scopus)

Abstract

A lot of Pull Requests (PRs) appear in Github everyday, and thus it is a very important work to review these PRs quickly in Github. Labeling PRs according to the PRs classification can improve the success rate and the review efficiency. However, recent research works have shown that most of the PRs are not labeled, and if the PR is labeled, it is done manually. To solve this problem, we propose a supervised classification model combined with supervised topics model and Naive Bayes classifier, which can make the PR be classified automatically. The method creates a one-one relationship between labels and PRs, and the approach classifies most PRs automatically with the only label which record the closest topic of PRs. The experimental results show that the proposed model can reach a precision of 60% in majority situation. The proposed model may support a better result via adjusting the parameters in case.

Original language	English
Title of host publication	2018 IEEE International Conference on Communications (ICC)
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781538631812
ISBN (Print)	9781538631805
DOIs	https://doi.org/10.1109/ICC.2018.8422103
Publication status	Published - 30 Jul 2018
Event	2018 IEEE International Conference on Communications (ICC) - Kansas City, United States Duration: 20 May 2018 → 24 May 2018 https://icc2018.ieee-icc.org/index.html (Link to conference website)

Publication series

Name	IEEE International Conference on Communications
Volume	2018-May
ISSN (Print)	1550-3607

Conference

Conference	2018 IEEE International Conference on Communications (ICC)
Abbreviated title	IEEE ICC 2018
Country/Territory	United States
City	Kansas City
Period	20/05/18 → 24/05/18
Internet address	https://icc2018.ieee-icc.org/index.html (Link to conference website)

ASJC Scopus subject areas

Computer Networks and Communications
Electrical and Electronic Engineering

Documents and Links

10.1109/ICC.2018.8422103

Cite this

@inproceedings{366a1c8158c644ffa17def956c42a92d,

title = "NBSL: a supervised classification model of pull request in GitHub",

abstract = "A lot of Pull Requests (PRs) appear in Github everyday, and thus it is a very important work to review these PRs quickly in Github. Labeling PRs according to the PRs classification can improve the success rate and the review efficiency. However, recent research works have shown that most of the PRs are not labeled, and if the PR is labeled, it is done manually. To solve this problem, we propose a supervised classification model combined with supervised topics model and Naive Bayes classifier, which can make the PR be classified automatically. The method creates a one-one relationship between labels and PRs, and the approach classifies most PRs automatically with the only label which record the closest topic of PRs. The experimental results show that the proposed model can reach a precision of 60% in majority situation. The proposed model may support a better result via adjusting the parameters in case.",

author = "Song Yu and Li Xu and Yan Zhang and Jinsong Wu and Zhifang Liao and Yanbing Li",

note = "Funding Information: This work is supported by the Fundamental Research Funds for Central Universities of the Central South University(No.2017zzts600) and Chile Conicyt FONDECYT Regular 2018, ”Big data for sustainable smart cities with the aids of computational. intelligence”; 2018 IEEE International Conference on Communications (ICC), IEEE ICC 2018 ; Conference date: 20-05-2018 Through 24-05-2018",

year = "2018",

month = jul,

day = "30",

doi = "10.1109/ICC.2018.8422103",

language = "English",

isbn = "9781538631805",

series = "IEEE International Conference on Communications",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "2018 IEEE International Conference on Communications (ICC)",

address = "United States",

url = "https://icc2018.ieee-icc.org/index.html",

}

Yu, S, Xu, L, Zhang, Y, Wu, J, Liao, Z & Li, Y 2018, NBSL: a supervised classification model of pull request in GitHub. in 2018 IEEE International Conference on Communications (ICC)., 8422103, IEEE International Conference on Communications, vol. 2018-May, Institute of Electrical and Electronics Engineers Inc., 2018 IEEE International Conference on Communications (ICC), Kansas City, Missouri, United States, 20/05/18. https://doi.org/10.1109/ICC.2018.8422103

NBSL: a supervised classification model of pull request in GitHub. / Yu, Song; Xu, Li; Zhang, Yan et al.
2018 IEEE International Conference on Communications (ICC). Institute of Electrical and Electronics Engineers Inc., 2018. 8422103 (IEEE International Conference on Communications; Vol. 2018-May).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - NBSL: a supervised classification model of pull request in GitHub

AU - Yu, Song

AU - Xu, Li

AU - Zhang, Yan

AU - Wu, Jinsong

AU - Liao, Zhifang

AU - Li, Yanbing

N1 - Funding Information: This work is supported by the Fundamental Research Funds for Central Universities of the Central South University(No.2017zzts600) and Chile Conicyt FONDECYT Regular 2018, ”Big data for sustainable smart cities with the aids of computational. intelligence”

PY - 2018/7/30

Y1 - 2018/7/30

N2 - A lot of Pull Requests (PRs) appear in Github everyday, and thus it is a very important work to review these PRs quickly in Github. Labeling PRs according to the PRs classification can improve the success rate and the review efficiency. However, recent research works have shown that most of the PRs are not labeled, and if the PR is labeled, it is done manually. To solve this problem, we propose a supervised classification model combined with supervised topics model and Naive Bayes classifier, which can make the PR be classified automatically. The method creates a one-one relationship between labels and PRs, and the approach classifies most PRs automatically with the only label which record the closest topic of PRs. The experimental results show that the proposed model can reach a precision of 60% in majority situation. The proposed model may support a better result via adjusting the parameters in case.

AB - A lot of Pull Requests (PRs) appear in Github everyday, and thus it is a very important work to review these PRs quickly in Github. Labeling PRs according to the PRs classification can improve the success rate and the review efficiency. However, recent research works have shown that most of the PRs are not labeled, and if the PR is labeled, it is done manually. To solve this problem, we propose a supervised classification model combined with supervised topics model and Naive Bayes classifier, which can make the PR be classified automatically. The method creates a one-one relationship between labels and PRs, and the approach classifies most PRs automatically with the only label which record the closest topic of PRs. The experimental results show that the proposed model can reach a precision of 60% in majority situation. The proposed model may support a better result via adjusting the parameters in case.

U2 - 10.1109/ICC.2018.8422103

DO - 10.1109/ICC.2018.8422103

M3 - Conference contribution

AN - SCOPUS:85051436102

SN - 9781538631805

T3 - IEEE International Conference on Communications

BT - 2018 IEEE International Conference on Communications (ICC)

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2018 IEEE International Conference on Communications (ICC)

Y2 - 20 May 2018 through 24 May 2018

ER -

NBSL: a supervised classification model of pull request in GitHub

Abstract

Publication series

Conference

ASJC Scopus subject areas

Documents and Links

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