{"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/mapping-language-to-code-in-programmatic","title":"Mapping Language to Code in Programmatic Context","arxiv_id":"1808.09588","date":"2018-08-29","proceeding":"EMNLP 2018 10","authors":["Srinivasan Iyer","Ioannis Konstas","Alvin Cheung","Luke Zettlemoyer"],"abstract":"Source code is rarely written in isolation. It depends significantly on the\nprogrammatic context, such as the class that the code would reside in. To study\nthis phenomenon, we introduce the task of generating class member functions\ngiven English documentation and the programmatic context provided by the rest\nof the class. This task is challenging because the desired code can vary\ngreatly depending on the functionality the class provides (e.g., a sort\nfunction may or may not be available when we are asked to \"return the smallest\nelement\" in a particular member variable list). We introduce CONCODE, a new\nlarge dataset with over 100,000 examples consisting of Java classes from online\ncode repositories, and develop a new encoder-decoder architecture that models\nthe interaction between the method documentation and the class environment. We\nalso present a detailed error analysis suggesting that there is significant\nroom for future work on this task.","url_abs":"http://arxiv.org/abs/1808.09588v1","url_pdf":"http://arxiv.org/pdf/1808.09588v1.pdf","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":"mapping-language-to-code-in-programmatic","repo_url":"https://github.com/sriniiyer/concode","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"pytorch","reach":{"status":"ok","spdx":"MIT"}}],"tasks":[{"task_slug":"decoder","task_name":"Decoder"}],"methods":[],"datasets_introduced":[{"slug":"concode","name":"CONCODE","full_name":""}],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1808.09588","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1808.09588"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. 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