Static inference meets deep learning

Author:

Peng Yun1,Gao Cuiyun2,Li Zongjie2,Gao Bowei2,Lo David3,Zhang Qirun4,Lyu Michael1

Affiliation:

1. The Chinese University of Hong Kong, Hong Kong, China

2. Harbin Institute of Technology, Shenzhen, China

3. Singapore Management University, Singapore

4. Georgia Institute of Technology

Funder

the Research Grants Council of the Hong Kong Special Administrative Region, China

Publisher

ACM

Reference62 articles.

1. aldur. The return value at line 295 ., 2021 . https://github.com/aldur/MatasanoCrypto/blob/master/matasano/blocks.py. aldur. The return value at line 295., 2021. https://github.com/aldur/MatasanoCrypto/blob/master/matasano/blocks.py.

2. Typilus: neural type hints

3. Dynamic inference of static types for ruby

4. Towards Type Inference for JavaScript

5. Sheng Chen and Martin Erwig . Principal type inference for gadts. In Rastislav Bodík and Rupak Majumdar, editors , Proceedings of the 43rd Annual ACM SIGPLAN-SIGACT Symposium on Principles of Programming Languages, POPL 2016, St . Petersburg, FL, USA, January 20 - 22 , 2016 , pages 416 -- 428 . ACM, 2016. Sheng Chen and Martin Erwig. Principal type inference for gadts. In Rastislav Bodík and Rupak Majumdar, editors, Proceedings of the 43rd Annual ACM SIGPLAN-SIGACT Symposium on Principles of Programming Languages, POPL 2016, St. Petersburg, FL, USA, January 20 - 22, 2016, pages 416--428. ACM, 2016.

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