Pull Requests Acceptance: A Study Across Programming Languages

KUHEJDA, Ondřej and Bruno ROSSI. Pull Requests Acceptance: A Study Across Programming Languages. Online. In 49th Euromicro Conference Series on Software Engineering and Advanced Applications (SEAA2023). Not specified: IEEE, 2023, p. 378-385. ISBN 979-8-3503-4235-2. Available from: https://dx.doi.org/10.1109/SEAA60479.2023.00064.

Basic information

• Original name: Pull Requests Acceptance: A Study Across Programming Languages
• Authors: KUHEJDA, Ondřej (203 Czech Republic, belonging to the institution) and Bruno ROSSI (380 Italy, guarantor, belonging to the institution).
• Edition: Not specified, 49th Euromicro Conference Series on Software Engineering and Advanced Applications (SEAA2023), p. 378-385, 8 pp. 2023.
• Publisher: IEEE

Other information

• Original language: English
• Type of outcome: Proceedings paper
• Field of Study: 10200 1.2 Computer and information sciences
• Country of publisher: United States of America
• Confidentiality degree: is not subject to a state or trade secret
• Publication form: electronic version available online
• RIV identification code: RIV/00216224:14330/23:00131439
• Organization unit: Faculty of Informatics
• ISBN: 979-8-3503-4235-2
• ISSN: 2376-9521
• Doi: http://dx.doi.org/10.1109/SEAA60479.2023.00064
• Keywords in English: Source Code quality; Mining software repositories; Pull requests; Static code analysis
• Tags: core_B, firank_B
• Tags: International impact, Reviewed

Abstract

Context: The pull-based development is a modern way to support distributed software development, helping to produce high-quality software with increased involvement from the software development community. Objectives: We investigate the effect of source code quality on Pull Request (PR) acceptance in different programming languages, looking at the quality flaws that can be more relevant. Method: We mine software repositories to analyze over 40K PRs from 100 open-source projects in five different programming languages: Python, Java, Kotlin, Haskell, and C/C++. The code quality of the individual PRs was evaluated using static code analysis. Quality flaws were inputted into classification models to predict PRs acceptance and evaluate the fitting. Results: There is a low impact of code quality on PRs acceptance. No major quality flaws can be used to predict reliably PRs acceptance. Conclusion: Source code quality plays a marginal role in accepting PRs in the analyzed projects. Additional factors might impact the acceptance of PRs, such as the reputation and popularity of the submitters.

Links

• CZ.02.1.01/0.0/0.0/16_019/0000822, interní kód MU(CEP code: EF16_019/0000822): Name: Centrum excelence pro kyberkriminalitu, kyberbezpečnost a ochranu kritických informačních infrastruktur (Acronym: C4e)

Investor: Ministry of Education, Youth and Sports of the CR, CyberSecurity, CyberCrime and Critical Information Infrastructures Center of Excellence, Priority axis 1: Strengthening capacities for high-quality research

• EF16_019/0000822, research and development project: Name: Centrum excelence pro kyberkriminalitu, kyberbezpečnost a ochranu kritických informačních infrastruktur
• 90254, large research infrastructures: Name: e-INFRA CZ II