Information retrieval versus deep learning approaches for generating traceability links in bilingual projects-Reference-Cited by-同舟云学术

Information retrieval versus deep learning approaches for generating traceability links in bilingual projects

Published:2021-10-22 Issue:1 Volume:27 Page:
ISSN:1382-3256
Container-title:Empirical Software Engineering
language:en
Short-container-title:Empir Software Eng

Author:

Lin Jinfeng,Liu Yalin,Cleland-Huang Jane

Funder

National Science Foundation

Publisher

Springer Science and Business Media LLC

Subject

Software

Link

https://link.springer.com/content/pdf/10.1007/s10664-021-10050-0.pdf

Reference78 articles.

1. EF EPI (2019) EF English Proficiency Index

2. Fasttext (2021) Word vectors for 157 languages ⋅ fasttext

3. Double Blinded (2020) All information is blinded due to current submission under double blind review. the paper is available upon request to the associate editors of the msr emse special edition

4. Abufardeh S, Magel K (2010) The impact of global software cultural and linguistic aspects on global software development process (gsd): Issues and challenges. In: 4th International conference on new trends in information science and service science. pp 133–138

5. Ali N, Guéhéneuc Y, Antoniol G (2013) Trustrace: Mining software repositories to improve the accuracy of requirement traceability links. IEEE Trans Softw Eng 39(5):725–741

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