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Documents authored by Sutton, Charles

Document
DOI: 10.4230/DagRep.13.2.20
Programming Language Processing (Dagstuhl Seminar 23062)

Authors: Michael Pradel, Baishakhi Ray, Charles Sutton, and Eran Yahav

Published in: Dagstuhl Reports, Volume 13, Issue 2 (2023)

Abstract
This report documents the program and the outcomes of Dagstuhl Seminar 23062 "Programming Language Processing" (PLP). The seminar brought together researchers and practitioners from three communities-software engineering, programming languages, and natural language processing- providing a unique opportunity for cross-fertilization and inter-disciplinary progress. We discussed machine learning models of code, integrating learning-based and traditional program analysis, and learning from natural language information associated with software. The seminar lead to a better understanding of the commonalities and differences between natural and programming languages, and an understanding of the challenges and opportunities in industry adoption of PLP.
Cite as

Michael Pradel, Baishakhi Ray, Charles Sutton, and Eran Yahav. Programming Language Processing (Dagstuhl Seminar 23062). In Dagstuhl Reports, Volume 13, Issue 2, pp. 20-32, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@Article{pradel_et_al:DagRep.13.2.20,
  author =	{Pradel, Michael and Ray, Baishakhi and Sutton, Charles and Yahav, Eran},
  title =	{{Programming Language Processing (Dagstuhl Seminar 23062)}},
  pages =	{20--32},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2023},
  volume =	{13},
  number =	{2},
  editor =	{Pradel, Michael and Ray, Baishakhi and Sutton, Charles and Yahav, Eran},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.13.2.20},
  URN =		{urn:nbn:de:0030-drops-191799},
  doi =		{10.4230/DagRep.13.2.20},
  annote =	{Keywords: ML4PL, ML4SE, Neural Software Analysis}
}
Document
DOI: 10.4230/DagRep.5.11.90
Programming with "Big Code" (Dagstuhl Seminar 15472)

Authors: William W. Cohen, Charles Sutton, and Martin T. Vechev

Published in: Dagstuhl Reports, Volume 5, Issue 11 (2016)

Abstract
This report documents the program and the outcomes of Dagstuhl Seminar 15472 "Programming with "Big Code"". "Big Code" is a term used to refer to the increasing availability of the millions of programs found in open source repositories such as GitHub, BitBucket, and others. With this availability, an opportunity appears in developing new kinds of statistical programming tools that learn and leverage the effort that went into building, debugging and testing the programs in "Big Code" in order to solve various important and interesting programming challenges. Developing such statistical tools however requires deep expertise across multiple areas of computer science including machine learning, natural language processing, programming languages and software engineering. Because of its highly inter-disciplinary nature, the seminar involved top experts from these fields who have worked on or are interested in the area. The seminar was successful in familiarizing the participants with recent developments in the area, bringing new understanding to different communities and outlining future research directions.
Cite as

William W. Cohen, Charles Sutton, and Martin T. Vechev. Programming with "Big Code" (Dagstuhl Seminar 15472). In Dagstuhl Reports, Volume 5, Issue 11, pp. 90-102, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)

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@Article{cohen_et_al:DagRep.5.11.90,
  author =	{Cohen, William W. and Sutton, Charles and Vechev, Martin T.},
  title =	{{Programming with "Big Code" (Dagstuhl Seminar 15472)}},
  pages =	{90--102},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2016},
  volume =	{5},
  number =	{11},
  editor =	{Cohen, William W. and Sutton, Charles and Vechev, Martin T.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.5.11.90},
  URN =		{urn:nbn:de:0030-drops-57665},
  doi =		{10.4230/DagRep.5.11.90},
  annote =	{Keywords: machine learning, natural language processing, programming languages, software engineering, statistical programming tools}
}
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