The NLBSE'23 Tool Competition-Reference-Cited by-同舟云学术

The NLBSE'23 Tool Competition

Published:2023-05 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE/ACM 2nd International Workshop on Natural Language-Based Software Engineering (NLBSE)
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Author:

Kallis Rafael¹,Izadi Maliheh²,Pascarella Luca³,Chaparro Oscar⁴,Rani Pooja⁵

Affiliation:

1. Rafael Kallis Consulting,Zurich,Switzerland

2. Delft University of Technology,Delft,The Netherlands

3. ETH Zurich,Zurich,Switzerland

4. College of William & Mary,Williamsburg,USA

5. University of Zurich,Zurich,Switzerland

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10189115/10189122/10189143.pdf?arnumber=10189143

Reference49 articles.

1. Few-Shot Learning for Issue Report Classification

2. An Intelligent Tool for Classifying Issue Reports;laiq;Proceedings of The 2nd International Workshop on Natural Language-based Software Engineering (NLBSE'23),2023

3. Performance Comparison of Binary Machine Learning Classifiers in Identifying Code Comment Types: An Exploratory Study

4. STACC: Code Comment Classification using Sentence Transformers;al-kaswan;Proceedings of The 2nd International Workshop on Natural Language-based Software Engineering (NLBSE'23),2023

5. A decade of code comment quality assessment: A systematic literature review

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1. The NLBSE'24 Tool Competition;Proceedings of the Third ACM/IEEE International Workshop on NL-based Software Engineering;2024-04-20

2. Leveraging GPT-like LLMs to Automate Issue Labeling;Proceedings of the 21st International Conference on Mining Software Repositories;2024-04-15

3. An Intelligent Tool for Classifying Issue Reports;2023 IEEE/ACM 2nd International Workshop on Natural Language-Based Software Engineering (NLBSE);2023-05