A large scale study of multiple programming languages and code quality
Nowadays, most software use multiple programming languages to implement certain functionalities based on the strengths and weaknesses of different languages. Researchers in the past have studied the impact of independent programming languages on software quality, however, there has been little or no...
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sg-smu-ink.sis_research-47572018-06-01T05:20:57Z A large scale study of multiple programming languages and code quality KOCHHAR, Pavneet Singh WIJEDASA, Withthige Dinusha Ruchira LO, David Nowadays, most software use multiple programming languages to implement certain functionalities based on the strengths and weaknesses of different languages. Researchers in the past have studied the impact of independent programming languages on software quality, however, there has been little or no research on the impact of multiple languages on the quality of software. Does the use of multiple languages cause more bugs? Are certain languages when used with other languages make software more bug prone? What are the relationships between multi-language usage and various bug categories? In this study, we perform a large scale empirical investigation to shed light on the answers to these questions. We gather a large dataset consisting of popular projects from GitHub (628 projects, 85 million SLOC, 134 thousand authors, 3 million commits, in 17 languages) to understand the impact of using multiple languages on software quality. We build multiple regression models to study the effects of using different languages on the number of bug fixing commits while controlling for factors such as project size, team size, project age and the number of commits. Our results show that in general implementing a project with more languages has a significant effect on project quality, as it increases defect proneness. Moreover, we find specific languages that are statistically significantly more defect prone when they are used in a multi-language setting. These include popular languages like C++, Objective-C, and Java. Furthermore, we note that the use of more languages significantly increases bug proneness across all bug categories. The effect is strongest for memory, concurrency, and algorithm bugs. 2016-03-01T08:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/3755 info:doi/10.1109/SANER.2016.112 https://ink.library.smu.edu.sg/context/sis_research/article/4757/viewcontent/1855a563.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 Computer bugs Java Programming Software quality Google Software Engineering |
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Computer bugs Java Programming Software quality Software Engineering KOCHHAR, Pavneet Singh WIJEDASA, Withthige Dinusha Ruchira LO, David A large scale study of multiple programming languages and code quality |
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Nowadays, most software use multiple programming languages to implement certain functionalities based on the strengths and weaknesses of different languages. Researchers in the past have studied the impact of independent programming languages on software quality, however, there has been little or no research on the impact of multiple languages on the quality of software. Does the use of multiple languages cause more bugs? Are certain languages when used with other languages make software more bug prone? What are the relationships between multi-language usage and various bug categories? In this study, we perform a large scale empirical investigation to shed light on the answers to these questions. We gather a large dataset consisting of popular projects from GitHub (628 projects, 85 million SLOC, 134 thousand authors, 3 million commits, in 17 languages) to understand the impact of using multiple languages on software quality. We build multiple regression models to study the effects of using different languages on the number of bug fixing commits while controlling for factors such as project size, team size, project age and the number of commits. Our results show that in general implementing a project with more languages has a significant effect on project quality, as it increases defect proneness. Moreover, we find specific languages that are statistically significantly more defect prone when they are used in a multi-language setting. These include popular languages like C++, Objective-C, and Java. Furthermore, we note that the use of more languages significantly increases bug proneness across all bug categories. The effect is strongest for memory, concurrency, and algorithm bugs. |
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KOCHHAR, Pavneet Singh WIJEDASA, Withthige Dinusha Ruchira LO, David |
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KOCHHAR, Pavneet Singh WIJEDASA, Withthige Dinusha Ruchira LO, David |
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KOCHHAR, Pavneet Singh |
title |
A large scale study of multiple programming languages and code quality |
title_short |
A large scale study of multiple programming languages and code quality |
title_full |
A large scale study of multiple programming languages and code quality |
title_fullStr |
A large scale study of multiple programming languages and code quality |
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A large scale study of multiple programming languages and code quality |
title_sort |
large scale study of multiple programming languages and code quality |
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Institutional Knowledge at Singapore Management University |
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2016 |
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https://ink.library.smu.edu.sg/sis_research/3755 https://ink.library.smu.edu.sg/context/sis_research/article/4757/viewcontent/1855a563.pdf |
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