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Programming languages & software engineering

Building programming languages, tools, and software engineering techniques that make software more reliable, secure, and productive.

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公開日

動画

5 Lessons Learned Contributing to an Ethereum Open Source Project

November 1, 2022 | Austin Akers

5 Lessons Learned Contributing to an Ethereum Open Source Project – Austin Akers

16:32

公開日

Understanding Skills for OSS Communities on GitHub

Jenny T. Liang, Tom Zimmermann, Denae Ford

ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE) | November 2022

プロジェクトプロジェクト

公開日

Program Merge Conflict Resolution via Neural Transformers

Alexey Svyatkovskiy, Sarah Fakhoury, Negar Ghorbani, Todd Mytkowicz, Christian Bird, Jinu Jang, Neel Sundaresan, Shuvendu Lahiri, Elizabeth Dinella

The ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE ’22) | November 2022

プロジェクトプロジェクト

公開日

NL2Viz: Natural Language to Visualization via Constrained Syntax-Guided Synthesis

Zhengkai Wu, Vu Le, Ashish Tiwari, Sumit Gulwani, Arjun Radhakrishna, Ivan Radicek, Gustavo Soares, Xinyu Wang, Zhenwen Li, Tao Xie

FSE | November 2022

公開日

FlakeRepro: Automated and Efficient Reproduction of Concurrency-Related Flaky Tests

Tanakorn Leesatapornwongsa, Xiang Ren , Suman Nath

ESEC/FSE | November 2022

プロジェクト

公開日

How to Fight Production Incidents? An Empirical Study on a Large-scale Cloud Service

Supriyo GHOSH, Manish Shetty, Chetan Bansal, Suman Nath

SoCC 2022 | November 2022

Best Paper Award

プロジェクト

公開日

When Language Model Meets Private Library

Daoguang Zan, Bei Chen, Zeqi Lin, Bei Guan, Yongji Wang, Jian-Guang Lou

EMNLP 2022 | October 2022

公開日

A large-scale empirical study of commit message generation: models, datasets and evaluation

Wei Tao, Yanlin Wang, Ensheng Shi, Lun Du, Shi Han, Hongyu Zhang, Dongmei Zhang, Wenqiang Zhang

Empirical Software Engineering | October 2022

公開日

Soft-Labeled Contrastive Pre-Training for Function-Level Code Representation

Xiaonan Li, Daya Guo, Yeyun Gong, Yun Lin, Yelong Shen, Xipeng Qiu, Daxin Jiang (姜大昕), Weizhu Chen, Nan Duan

EMNLP 2022 | October 2022

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NatGen – Pretrained Models

Pre-trained Generative Language models (e.g. PLBART, CodeT5, SPT-Code) for source code yielded strong results on several tasks in the past few years, including code generation and translation. These models have adopted varying pre-training objectives to…

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