2 Search Results for "Vechev, Martin"


Document
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-dev.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}
}
Document
Programming with "Big Code": Lessons, Techniques and Applications

Authors: Pavol Bielik, Veselin Raychev, and Martin Vechev

Published in: LIPIcs, Volume 32, 1st Summit on Advances in Programming Languages (SNAPL 2015)


Abstract
Programming tools based on probabilistic models of massive codebases (aka "Big Code") promise to solve important programming tasks that were difficult or practically infeasible to address before. However, building such tools requires solving a number of hard problems at the intersection of programming languages, program analysis and machine learning. In this paper we summarize some of our experiences and insights obtained by developing several such probabilistic systems over the last few years (some of these systems are regularly used by thousands of developers worldwide). We hope these observations can provide a guideline for others attempting to create such systems. We also present a prediction approach we find suitable as a starting point for building probabilistic tools, and discuss a practical framework implementing this approach, called Nice2Predict. We release the Nice2Predict framework publicly - the framework can be immediately used as a basis for developing new probabilistic tools. Finally, we present programming applications that we believe will benefit from probabilistic models and should be investigated further.

Cite as

Pavol Bielik, Veselin Raychev, and Martin Vechev. Programming with "Big Code": Lessons, Techniques and Applications. In 1st Summit on Advances in Programming Languages (SNAPL 2015). Leibniz International Proceedings in Informatics (LIPIcs), Volume 32, pp. 41-50, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2015)


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@InProceedings{bielik_et_al:LIPIcs.SNAPL.2015.41,
  author =	{Bielik, Pavol and Raychev, Veselin and Vechev, Martin},
  title =	{{Programming with "Big Code": Lessons, Techniques and Applications}},
  booktitle =	{1st Summit on Advances in Programming Languages (SNAPL 2015)},
  pages =	{41--50},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-939897-80-4},
  ISSN =	{1868-8969},
  year =	{2015},
  volume =	{32},
  editor =	{Ball, Thomas and Bodík, Rastislav and Krishnamurthi, Shriram and Lerner, Benjamin S. and Morriset, Greg},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.SNAPL.2015.41},
  URN =		{urn:nbn:de:0030-drops-50152},
  doi =		{10.4230/LIPIcs.SNAPL.2015.41},
  annote =	{Keywords: probabilistic tools, probabilistic inference and learning, program analysis, open-source software}
}
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