2018年NLP软件工程研讨会 Workshop on NLP for Software Engineering

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活动简介

The proliferation of open-source projects has led to large amounts of source code and related artifacts: arguably, the rich and open resources associated with software — including open source repositories, Q/A sites, change histories, and communications between developers — are the richest and most detailed information resource for any technical area. Recently it has been discovered that natural, human-produced software has many interesting statistical regularities. As a consequence, code corpora, just like natural language corpora, are amenable to statistical modeling, and a number of software tasks such as coding, testing, porting, bug-patching and others are potentially enhanced by the use of these statistical models.

征稿信息

TopicsThis interdisciplinary workshop will explore issues related to the statistical modeling of software corpora, including topics such as modeling repetitiveness in source code; use of language models for the code suggestion in IDEs; using probabilistic grammars to mine programming idioms; statistical methods for type inference in a dynamically typed languages; statistical machine translation for porting applications between programming languages, or minifying Javascript; using statistical language models to find bugs; or statistical methods for automatic code patching, code summarization, code retrieval, code annotation, or test generation.The workshop follows several earlier workshops on this topic at Microsoft Research, Dagstuhl event, and SIGSOFT FSE. From NSF, some funding is available for US travelers to the workshop, especially students and members of under-represented groups, and researchers that might not normally attend AAAI.