Machine/Deep Learning for Software Engineering: A Systematic Literature Review-Reference-Cited by-同舟云学术

Machine/Deep Learning for Software Engineering: A Systematic Literature Review

Published:2023-03-01 Issue:3 Volume:49 Page:1188-1231
ISSN:0098-5589
Container-title:IEEE Transactions on Software Engineering
language:
Short-container-title:IIEEE Trans. Software Eng.

Author:

Wang Simin¹^ORCID,Huang Liguo¹^ORCID,Gao Amiao¹,Ge Jidong²^ORCID,Zhang Tengfei²,Feng Haitao²^ORCID,Satyarth Ishna¹^ORCID,Li Ming²,Zhang He²^ORCID,Ng Vincent³^ORCID

Affiliation:

1. Department of Computer Science, Southern Methodist University, Dallas, TX, USA

2. Nanjing University, Nanjing, Jiangsu, China

3. Human Language Technology Research Institute, University of Texas at Dallas, Richardson, TX, USA

Funder

National Science Foundation

NSF of Jiangsu Province

Nanjing University

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Software

Link

https://ieeexplore.ieee.org/ielam/32/10070338/9772253-aam.pdf

Reference402 articles.

1. A Coefficient of Agreement for Nominal Scales

2. S EADS

3. How to “DODGE” Complex Software Analytics

4. Evaluation and Measurement of Software Process Improvement—A Systematic Literature Review

5. CoCoNuT: combining context-aware neural translation models using ensemble for program repair

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