{"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/a-parallel-corpus-of-python-functions-and","title":"A parallel corpus of Python functions and documentation strings for automated code documentation and code generation","arxiv_id":"1707.02275","date":"2017-07-07","proceeding":"IJCNLP 2017 11","authors":["Antonio Valerio Miceli Barone","Rico Sennrich"],"abstract":"Automated documentation of programming source code and automated code\ngeneration from natural language are challenging tasks of both practical and\nscientific interest. Progress in these areas has been limited by the low\navailability of parallel corpora of code and natural language descriptions,\nwhich tend to be small and constrained to specific domains.\n  In this work we introduce a large and diverse parallel corpus of a hundred\nthousands Python functions with their documentation strings (\"docstrings\")\ngenerated by scraping open source repositories on GitHub. We describe baseline\nresults for the code documentation and code generation tasks obtained by neural\nmachine translation. We also experiment with data augmentation techniques to\nfurther increase the amount of training data.\n  We release our datasets and processing scripts in order to stimulate research\nin these areas.","url_abs":"http://arxiv.org/abs/1707.02275v1","url_pdf":"http://arxiv.org/pdf/1707.02275v1.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":"a-parallel-corpus-of-python-functions-and","repo_url":"https://github.com/Avmb/code-docstring-corpus","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":{"status":"unanswered"}},{"paper_slug":"a-parallel-corpus-of-python-functions-and","repo_url":"https://github.com/EdinburghNLP/code-docstring-corpus","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"a-parallel-corpus-of-python-functions-and","repo_url":"https://github.com/ICSEG/M2TS","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"unanswered"}},{"paper_slug":"a-parallel-corpus-of-python-functions-and","repo_url":"https://github.com/YUEXIUG/M2TS","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"unanswered"}},{"paper_slug":"a-parallel-corpus-of-python-functions-and","repo_url":"https://github.com/transm2/mmf3","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"unanswered"}},{"paper_slug":"a-parallel-corpus-of-python-functions-and","repo_url":"https://github.com/transms/m2ts","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"unanswered"}}],"tasks":[{"task_slug":"code-generation","task_name":"Code Generation"},{"task_slug":"data-augmentation","task_name":"Data Augmentation"},{"task_slug":"machine-translation","task_name":"Machine Translation"},{"task_slug":"translation","task_name":"Translation"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1707.02275","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1707.02275"}},"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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