Continuous integration and delivery (CI/CD) are nowadays at the core of software development. Their benefits come at the cost of setting up and maintaining the CI/CD pipeline, which require knowledge and skills often orthogonal to those entailed in other software-related tasks. While several recommender systems have been proposed to support developers across a variety of tasks, little automated support is available when it comes to setting up and maintaining CI/CD pipelines. We present GH-WCOM (GitHub Workflow COMpletion), a Transformer-based approach supporting developers in writing a specific type of CI/CD pipelines, namely GitHub workflows. To deal with such a task, we designed an abstraction process to help the learning of the transformer while still making GH-WCOM able to recommend very peculiar workflow elements such as tool options and scripting elements. Our empirical study shows that GH-WCOM provides up to 34.23% correct predictions, and the model’s confidence is a reliable proxy for the recommendations’ correctness likelihood.
Wed 17 AprDisplayed time zone: Lisbon change
14:00 - 15:30 | LLM, NN and other AI technologies 1Journal-first Papers / Research Track / New Ideas and Emerging Results at Luis de Freitas Branco Chair(s): Shin Yoo Korea Advanced Institute of Science and Technology | ||
14:00 15mTalk | EGFE: End-to-end Grouping of Fragmented Elements in UI Designs with Multimodal Learning Research Track Liuqing Chen Zhejiang University, Yunnong Chen Zhejiang University, Shuhong Xiao , Yaxuan Song Zhejiang University, Lingyun Sun Zhejiang University, Yankun Zhen Alibaba Group, Tingting Zhou Alibaba Group, Yanfang Chang Alibaba Group Link to publication Pre-print Media Attached File Attached | ||
14:15 15mTalk | A Comprehensive Study of Learning-based Android Malware Detectors under Challenging Environments Research Track Gao Cuiying Huazhong University of Science and Technology, Gaozhun Huang Huazhong University of Science and Technology, Heng Li Huazhong University of Science and Technology, Bang Wu Huazhong University of Science and Technology, Yueming Wu Nanyang Technological University, Wei Yuan Huazhong University of Science and Technology | ||
14:30 15mTalk | Toward Automatically Completing GitHub Workflows Research Track Antonio Mastropaolo Università della Svizzera italiana, Fiorella Zampetti University of Sannio, Italy, Gabriele Bavota Software Institute @ Università della Svizzera Italiana, Massimiliano Di Penta University of Sannio, Italy Pre-print | ||
14:45 15mTalk | UniLog: Automatic Logging via LLM and In-Context Learning Research Track Junjielong Xu The Chinese University of Hong Kong, Shenzhen, Ziang Cui Southeast University, Yuan Zhao Peking University, Xu Zhang Microsoft Research, Shilin He Microsoft Research, Pinjia He Chinese University of Hong Kong, Shenzhen, Liqun Li Microsoft Research, Yu Kang Microsoft Research, Qingwei Lin Microsoft, Yingnong Dang Microsoft Azure, Saravan Rajmohan Microsoft 365, Dongmei Zhang Microsoft Research | ||
15:00 7mTalk | Self-Supervised Learning to Prove Equivalence Between Straight-Line Programs via Rewrite Rules Journal-first Papers Steve Kommrusch Leela AI, Martin Monperrus KTH Royal Institute of Technology, Louis-Noël Pouchet Colorado State University | ||
15:07 7mTalk | NLP-based Automated Compliance Checking of Data Processing Agreements against GDPR Journal-first Papers Orlando Amaral University of Luxembourg, Muhammad Ilyas Azeem University of Luxembourg, Sallam Abualhaija University of Luxembourg, Lionel Briand University of Ottawa, Canada; Lero centre, University of Limerick, Ireland | ||
15:14 7mTalk | Exploring ChatGPT for Toxicity Detection in GitHub New Ideas and Emerging Results | ||