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|Acronym=NL+SE 2016 | |Acronym=NL+SE 2016 | ||
|Title=NL+SE 2016 : Natural language processing and software engineering | |Title=NL+SE 2016 : Natural language processing and software engineering | ||
+ | |Single Day Event=no | ||
+ | |Start Date=2016/11/13 | ||
+ | |End Date=2016/11/13 | ||
+ | |Event Status=as scheduled | ||
+ | |Event Mode=on site | ||
+ | |City=Seattle | ||
+ | |Country=Country:US | ||
+ | |Academic Field=Software Engineering | ||
+ | |Official Website=http://nlse-fse.github.io/ | ||
+ | |Submission Link=easychair.org/conferences/?conf=nlse2016 | ||
|Type=Conference | |Type=Conference | ||
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|Has coordinator=Prem Devanbu, Tien N. Nguyen, Baishakhi Ray, Earl Barr, Christian Bird, | |Has coordinator=Prem Devanbu, Tien N. Nguyen, Baishakhi Ray, Earl Barr, Christian Bird, | ||
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|pageCreator=Liy1 | |pageCreator=Liy1 | ||
|pageEditor=User:Curator 86 | |pageEditor=User:Curator 86 | ||
|contributionType=1 | |contributionType=1 | ||
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}} | }} | ||
+ | {{Event Deadline | ||
+ | |Submission Deadline=2016/08/08 | ||
+ | }} | ||
+ | {{Event Metric}} | ||
+ | {{S Event}} | ||
Natural Language Processing (NLP) techniques and tools have become very powerful and are applicable in many domains. In the context of Software Engineering (SE), there are many promising opportunities for the application of NLP to be used to improve SE theory and practice. Recently, investigations have begun to unravel the extent to which large code corpora that can be retrieved from GitHub, StackOverflow, etc., are amenable to analysis using statistical NLP models and algorithms, so that the revolutionary advances in speech recognitions, translation, comprehension, etc. can be applied in SE. | Natural Language Processing (NLP) techniques and tools have become very powerful and are applicable in many domains. In the context of Software Engineering (SE), there are many promising opportunities for the application of NLP to be used to improve SE theory and practice. Recently, investigations have begun to unravel the extent to which large code corpora that can be retrieved from GitHub, StackOverflow, etc., are amenable to analysis using statistical NLP models and algorithms, so that the revolutionary advances in speech recognitions, translation, comprehension, etc. can be applied in SE. | ||
Latest revision as of 10:33, 16 December 2022
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Submission |
Seattle, United States of America
Natural Language Processing (NLP) techniques and tools have become very powerful and are applicable in many domains. In the context of Software Engineering (SE), there are many promising opportunities for the application of NLP to be used to improve SE theory and practice. Recently, investigations have begun to unravel the extent to which large code corpora that can be retrieved from GitHub, StackOverflow, etc., are amenable to analysis using statistical NLP models and algorithms, so that the revolutionary advances in speech recognitions, translation, comprehension, etc. can be applied in SE.
This workshop will bring together an international group of researchers in Statistical NLP, Programming Languages, Software Engineering and related fields for an intensive period of discussion and presentation of results in the area. We invite a range of researchers with both NLP and SE backgrounds to come together, discuss their research, establish datasets, tasks, and baselines, and generally help the field build momentum.
We invite short position papers, of at most 4 pages in length. Submissions will be reviewed primarily for relevance, will not appear in ACM Digital Library, and may be published subsequently elsewhere. A few of the submissions will be invited for presentation.