GitHubInclusifier: Finding and fixing non-inclusive language in GitHub Repositories
Non-inclusive language in software artefacts has been recognised as a serious problem. We describe a tool to find and fix non-inclusive language in a variety of GitHub repository artefacts. These include various README files, PDFs, code comments, and code. A wide variety of non-inclusive language including raceist, ageist, ableist, violent and others are located and issues created, tagging the artefacts for checking. Suggested fixes can be generated using third-party LLM APIs, and approved changes made to documents, including code refactorings, and commited to the repository.
The tool and evaluation data are available from: https://github.com/LiamTodd/github-inclusifier
The demo video is available at: https://www.youtube.com/watch?v=1z1QKdQg-nM
Fri 19 AprDisplayed time zone: Lisbon change
14:00 - 15:30 | Language Models and Generated Code 3Research Track / Demonstrations at Almada Negreiros Chair(s): Jie M. Zhang King's College London | ||
14:00 15mTalk | CoderEval: A Benchmark of Pragmatic Code Generation with Generative Pre-trained Models Research Track Hao Yu Peking University, Bo Shen Huawei Cloud Computing Technologies Co., Ltd., Dezhi Ran Peking University, Jiaxin Zhang Huawei Cloud Computing Technologies Co., Ltd., Qi Zhang Huawei Cloud Computing Technologies Co., Ltd., Yuchi Ma Huawei Cloud Computing Technologies CO., LTD., Guangtai Liang Huawei Cloud Computing Technologies, Ying Li School of Software and Microelectronics, Peking University, Beijing, China, Qianxiang Wang Huawei Technologies Co., Ltd, Tao Xie Peking University | ||
14:15 15mTalk | Inferring Data Preconditions from Deep Learning Models for Trustworthy Prediction in Deployment Research Track Shibbir Ahmed Iowa State University, Hongyang Gao Dept. of Computer Science, Iowa State University, Hridesh Rajan Iowa State University | ||
14:30 15mTalk | GrammarT5: Grammar-Integrated Pretrained Encoder-Decoder Neural Model for Code Research Track Qihao Zhu Peking University, Qingyuan Liang Peking University, Zeyu Sun Institute of Software, Chinese Academy of Sciences, Yingfei Xiong Peking University, Lu Zhang Peking University, Shengyu Cheng ZTE Corporation | ||
14:45 15mTalk | On Calibration of Pre-trained Code models Research Track DOI Media Attached | ||
15:00 15mTalk | Learning in the Wild: Towards Leveraging Unlabeled Data for Effectively Tuning Pre-trained Code Models Research Track Shuzheng Gao , Wenxin Mao Harbin Institute of Technology, Cuiyun Gao Harbin Institute of Technology, Li Li Beihang University, Xing Hu Zhejiang University, Xin Xia Huawei Technologies, Michael Lyu The Chinese University of Hong Kong | ||
15:15 7mTalk | GitHubInclusifier: Finding and fixing non-inclusive language in GitHub Repositories Demonstrations Liam Todd Monash University, John Grundy Monash University, Christoph Treude Singapore Management University Pre-print Media Attached | ||