{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/manytypes4typescript-a-comprehensive","title":"ManyTypes4TypeScript: A Comprehensive TypeScript Dataset for Sequence-Based Type Inference","arxiv_id":null,"date":"2022-10-17","proceeding":"International Conference on Mining Software Repositories 2022 10","authors":["Kevin Jesse","Premkumar T. Devanbu"],"abstract":"In this paper, we present ManyTypes4TypeScript, a very large\r\ncorpus for training and evaluating machine-learning models for\r\nsequence-based type inference in TypeScript. The dataset includes\r\nover 9 million type annotations, across 13,953 projects and 539,571\r\nfiles. The dataset is approximately 10x larger than analogous type\r\ninference datasets for Python, and is the largest available for TypeScript. We also provide API access to the dataset, which can be\r\nintegrated into any tokenizer and used with any state-of-the-art\r\nsequence-based model. Finally, we provide analysis and performance results for state-of-the-art code-specific models, for baselining. ManyTypes4TypeScript is available on Huggingface, Zenodo,\r\nand CodeXGLUE.","url_abs":"https://dl.acm.org/doi/10.1145/3524842.3528507","url_pdf":"https://dl.acm.org/doi/pdf/10.1145/3524842.3528507","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"manytypes4typescript-a-comprehensive","repo_url":"https://huggingface.co/kevinjesse/graphcodebert-MT4TS","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"type-prediction","task_name":"Type prediction"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/type-prediction-on-manytypes4typescript","task":"Type prediction","dataset":"ManyTypes4TypeScript","model":"GraphCodeBERT-MT4TS","rank_in_archive_order":2,"of":9,"metrics":{"Average Accuracy":"63.42"},"uses_additional_data":false}],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}