Potential Technical Debt and Its Resolution in Code Reviews: An Exploratory Study of the OpenStack and Qt Communities-Reference-Cited by-同舟云学术

Potential Technical Debt and Its Resolution in Code Reviews: An Exploratory Study of the OpenStack and Qt Communities

Published:2022-09-19 Issue: Volume: Page:
ISSN:
Container-title:ACM / IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM)
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Author:

Fu Liming¹,Liang Peng¹,Rasheed Zeeshan¹,Li Zengyang²,Tahir Amjed³,Han Xiaofeng⁴

Affiliation:

1. School of Computer Science, Wuhan University, China and Hubei Luojia Laboratory, China

2. School of Computer Science & Hubei Provincial Key Laboratory of Artificial Intelligence and Smart Learning, Central China Normal University, China

3. School of Mathematical and Computational Sciences, Massey University, New Zealand

4. Wuhan University, China and Hubei Luojia Laboratory, China

Funder

Hubei Provincial Natural Science Foundation of China

The Special Fund of Hubei Luojia Laboratory

National Natural Science Foundation of China

NZ SfTI National Science Challenge Grant

Publisher

ACM

Reference38 articles.

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2. Olga Baysal , Oleksii Kononenko , Reid Holmes , and Michael W. Godfrey . 2013 . The Influence of Non-technical Factors on Code Review . In Proceedings of the 20th Working Conference on Reverse Engineering (WCRE). IEEE, 122–131 . Olga Baysal, Oleksii Kononenko, Reid Holmes, and Michael W. Godfrey. 2013. The Influence of Non-technical Factors on Code Review. In Proceedings of the 20th Working Conference on Reverse Engineering (WCRE). IEEE, 122–131.

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5. Rafael Maiani de Mello , Roberto Oliveira , and Alessandro Garcia . 2017 . On the Influence of Human Factors for Identifying Code Smells: A Multi-Trial Empirical Study . In Proceedings of the 11th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM). IEEE, 68–77 . Rafael Maiani de Mello, Roberto Oliveira, and Alessandro Garcia. 2017. On the Influence of Human Factors for Identifying Code Smells: A Multi-Trial Empirical Study. In Proceedings of the 11th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM). IEEE, 68–77.

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