Automatic Programming


Automatic Programming

AITopics Original Links

Our approach to automatic programming is based on reuse of generic algorithms through views. A generic algorithm performs some task, such as sorting a linked list of records, based on abstract descriptions of the data on which the program operates. A view describes how actual application data corresponds to the abstract data as used in the generic algorithm. Given a view, a generic algorithm can be specialized by a compilation process to produce a version of the algorithm that performs the algorithm directly on the application data.


AI-Lab - Automatic Programming

AITopics Original Links

Our goal is automatic generation of computer programs from specifications that are much smaller and easier to write than ordinary programs. Generation of geometric programs specified by diagrams 2011 Yulin Li and Gordon S. Novak, Jr., In Proceedings of the 10th ACM international conference on Generative programming and component engineering, pp. Computer aided software design via inference and constraint propagation 2009 Gordon Novak, Integrated Computer-Aided Engineering, Vol. Knowledge Based Programming Using Abstract Data Types 1983 Gordon Novak, In Proc.


CS 394P: Automatic Programming

AITopics Original Links

The course consists of lectures for the first two-thirds of the semester. Homework problems and programming assignments illustrate the lecture material. The programs are not long; the intent is to gain some exposure to several kinds of programming systems. The latter part of the semester covers readings in the research literature; students are expected to present one or two papers to the class.


William A. Martin

AITopics Original Links

Professor Martin, whose main interest was in the practical application of artificial intelligence, was associated with the Laboratory for Computer Science and the Artificial Intelligence Laboratory at MIT. His work involved computer programs that embody various forms of expertise---mathematical, medical, management or linguistic---and the application of this expertise to practical ends. His system for symbolic mathematics is now used around the country by a large community of scientists. Professor Martin's interest in mangagement led him to the development of automatic programming techniques that are widely used.


Automatic Programming Assessments

#artificialintelligence

An ability to write functionally correct programs -- those that pass test cases? A seasoned interviewer would tell you that there is much more to writing code than passing test cases! For starters, we really care for how well a candidate understands the problem and approaches a solution than being able to write functionally correct code. Machine learning has helped solved many grading challenges -- spoken english, essay grading, program grading and math problem grading to cite a few examples.


Teddington-1.3-McCarthy.pdf

Classics (Collection 2)

His present interests are in the artificial intelligence problem, automatic programming and mathematical logic. These actions may include printing sentences, moving sentences on lists, and reinitiating the basic deduction process on these lists. It is not hard to make machines learn from experience to make simple changes in their behaviourof a kind which has been anticipated by the programmer. There is one known way of making a machine capable of learning arbitrary behaviour; thus to anticipate every kind of behaviour.


Teddington-1.3-McCarthy.pdf

Classics (Collection 2)

His present interests are in the artificial intelligence problem, automatic programming and mathematical logic. These actions may include printing sentences, moving sentences on lists, and reinitiating the basic deduction process on these lists. It is not hard to make machines learn from experience to make simple changes in their behaviourof a kind which has been anticipated by the programmer. There is one known way of making a machine capable of learning arbitrary behaviour; thus to anticipate every kind of behaviour.


Report 80-27.pdf

Classics (Collection 2)

Biological research has to date identified several mechanisms which change DNA (substitution, insertion, deletion, translocation, inversion, recombination, segregation, transposition, etc.) Current theories assume the basic process of evolution to be Early automatic programming systems were also built to work via this same "Random Generate and Test" process. Long before our three billion line genetic "program" evolved randomly, Nature may have happened upon a more powerful method.of "automatic programming", such as heuristic search: the accretion and use of knowledge to guide the mutation process. BLANK PAGE 2 Introduction Several biological mechanisms are known to result in altered DNA, mechanisms such as substitution, insertion, deletion, translocation, inversion, recombination, segregation, and transposition.


Report 80-27.pdf

Classics (Collection 2)

Biological research has to date identified several mechanisms which change DNA (substitution, insertion, deletion, translocation, inversion, recombination, segregation, transposition, etc.) Current theories assume the basic process of evolution to be Early automatic programming systems were also built to work via this same "Random Generate and Test" process. Long before our three billion line genetic "program" evolved randomly, Nature may have happened upon a more powerful method.of "automatic programming", such as heuristic search: the accretion and use of knowledge to guide the mutation process. BLANK PAGE 2 Introduction Several biological mechanisms are known to result in altered DNA, mechanisms such as substitution, insertion, deletion, translocation, inversion, recombination, segregation, and transposition.


Automatic Programming: A Tutorial on Formal Methodologies

Classics (Collection 2)

Some of the techniques generate code from formal input--output specifications while others work from examples of the target behaviour or from natural language input. The technologies of automatic programming thus include the fields that help move the programming experience along any of these dimensions: algorithm synthesis, programming language research, compiler theory, human factors, and others. This material is based on work supported by the Air Force Office of Scientific Research, Air Force Systems Command, USAF under Grant 81-0221 and the U.S. Army Research Office under Grant DAAG-29-84--K-0072. After completing the coverage of these formal methodologies, a short section mentions some work on the generation of programs from natural language input using artificial intelligence knowledge based systems.