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This paper presents an AI-assisted programming tool called Copilot for Xcode for program composition and design to support human software developers.
Prow: A step toward automatic program writing
Richard J Waldinger and Richard CT Lee · 1969
Earlier work this paper cites.
Toward automatic program synthesis
Zohar Manna and Richard J Waldinger · 1971
Earlier work this paper cites.
The humble programmer
Edsger W Dijkstra · 1972
Earlier work this paper cites.
Programming viewed as an engineering activity
Charles Rich, Howard E. Shrobe, Robert C. Waters, Gerald J. Sussman, and Carl E. Hewitt · 1978
Earlier work this paper cites.
Code generation in the programmer’s apprentice
Robert E. Handsaker · 1982
Earlier work this paper cites.
The disciplined use of simplifying assumptions
Charles Rich and Richard C. Waters · 1982
Earlier work this paper cites.
The programmer’s apprentice: Knowledge based program editing
Richard C. Waters · 1982
Earlier work this paper cites.
The programmer’s apprentice: a research overview
Charles Rich and Richard C. Waters · 1988
Earlier work this paper cites.
Statistical Language Learning
Eugene Charniak · 1996
Earlier work this paper cites.
Pattern matching for clone and concept detection
Kostas A Kontogiannis, Renator DeMori, Ettore Merlo, Michael Galler, and Morris Bernstein · 1996
Earlier work this paper cites.
Mining api patterns as partial orders from source code: From usage scenarios to specifications
Mithun Acharya, Tao Xie, Jian Pei, and Jun Xu · 2007
Earlier work this paper cites.
Defining the greatest common divisor
Edsger Wybe Dijkstra · 2007
Earlier work this paper cites.
A preliminary investigation into computer assisted programming
Edsger Wybe Dijkstra · 2007
Earlier work this paper cites.
How program history can improve code completion
Romain Robbes and Michele Lanza · 2008
Earlier work this paper cites.
Learning from examples to improve code completion systems
Marcel Bruch, Martin Monperrus, and Mira Mezini · 2009
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Towards automatically generating summary comments for java methods
Giriprasad Sridhara, Emily Hill, Divya Muppaneni, Lori Pollock, and K Vijay-Shanker · 2010
Earlier work this paper cites.
Generating parameter comments and integrating with method summaries
Giriprasad Sridhara, Lori Pollock, and K Vijay-Shanker · 2011
Earlier work this paper cites.
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Abram Hindle, Earl T Barr, Zhendong Su, Mark Gabel, and Premkumar Devanbu · 2012
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