Prompt-tuned Code Language Model as a Neural Knowledge Base for Type Inference in Statically-Typed Partial Code-Reference-Cited by-同舟云学术

Prompt-tuned Code Language Model as a Neural Knowledge Base for Type Inference in Statically-Typed Partial Code

Published:2022-10-10 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 37th IEEE/ACM International Conference on Automated Software Engineering
language:
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Author:

Huang Qing¹^ORCID,Yuan Zhiqiang¹^ORCID,Xing Zhenchang²^ORCID,Xu Xiwei³^ORCID,Zhu Liming⁴^ORCID,Lu Qinghua³^ORCID

Affiliation:

1. School of Computer Information Engineering, Jiangxi Normal University, China

2. CSIRO's Data61 & Australian National University, Australia

3. CSIRO's Data61, Australia

4. CSIRO's Data61 & School of CSE, UNSW, Australia

Funder

the National Nature Science Foundation of China under Grant

Postgraduate Innovation Fund Project of Jiangxi Province

the Nature Science Foundation of Jiangxi Province

the Science and technology Key project of Education Department of Jiangxi Province

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3551349.3556912

Reference92 articles.

1. Wasi Uddin Ahmad Saikat Chakraborty Baishakhi Ray and Kai-Wei Chang. 2020. A transformer-based approach for source code summarization. arXiv preprint arXiv:2005.00653(2020). Wasi Uddin Ahmad Saikat Chakraborty Baishakhi Ray and Kai-Wei Chang. 2020. A transformer-based approach for source code summarization. arXiv preprint arXiv:2005.00653(2020).

2. Raja Naeem Akram and Konstantinos Markantonakis. 2016. Challenges of security and trust of mobile devices as digital avionics component. In 2016 Integrated Communications Navigation and Surveillance (ICNS). 1C4-1-1C4-11. https://doi.org/10.1109/ICNSURV.2016.7486323 10.1109/ICNSURV.2016.7486323

3. Raja Naeem Akram and Konstantinos Markantonakis. 2016. Challenges of security and trust of mobile devices as digital avionics component. In 2016 Integrated Communications Navigation and Surveillance (ICNS). 1C4-1-1C4-11. https://doi.org/10.1109/ICNSURV.2016.7486323

4. A Survey of Machine Learning for Big Code and Naturalness

5. Miltiadis Allamanis Daniel Tarlow Andrew D. Gordon and Yi Wei. 2015. Bimodal Modelling of Source Code and Natural Language. In ICML. Miltiadis Allamanis Daniel Tarlow Andrew D. Gordon and Yi Wei. 2015. Bimodal Modelling of Source Code and Natural Language. In ICML.

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