Generative programming system and method employing focused...

Data processing: software development – installation – and managem – Software program development tool – Code generation

Reexamination Certificate

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

C717S107000

Reexamination Certificate

active

07577935

ABSTRACT:
A system and method may employ focused grammars to facilitate automated generation of computer programs. Such implementation of focused grammars enables a new form of symbolic regression referred to as generative programming or automated programming. The search through the space of possible programs may be guided by a streak search method in accordance with which identified candidate programs that improve on the current streak may be used to create focused grammars for directing an additional localized search. In some embodiments, candidate programs are generated by randomly traversing focused grammars from the starting rule, and subsequently through the grammars, until a complete candidate program parse tree has been constructed. Candidate programs may then be executed, for example, by an evaluator, which may employ an interpreter adapted for use in conjunction with a Stack Manipulation Language or other interpreted language.

REFERENCES:
patent: 4935877 (1990-06-01), Koza
patent: 5754860 (1998-05-01), McKeeman et al.
patent: 6083276 (2000-07-01), Davidson et al.
patent: 6246403 (2001-06-01), Tomm
patent: 6549943 (2003-04-01), Spring
patent: 6634019 (2003-10-01), Rice et al.
patent: 6754703 (2004-06-01), Spring
patent: 6954747 (2005-10-01), Wang et al.
patent: 6990654 (2006-01-01), Carroll, Jr.
patent: 2003/0200533 (2003-10-01), Roberts et al.
patent: 2004/0153995 (2004-08-01), Polonovski
Czarnecki, Krzystof. “Components and Generative Programming.” Foundations of Software Engineering: Proceedings of the 7th European software engineering conference held jointly with the 7th ACM SIGSOFT international symposium on Foundations of software engineering (1999): 2-19.
Ratle, Alain, Sebag, Michele. “A Novel Approach to Machine Discovery: Genetice Programming and Stochastic Grammars.” Proceedings from the 12th international Conference on Inductive Logic Programming 12(2002): 207-222.
Conor Ryan, et al. “Grammatical Evolution: Evolving Programs for an Arbitrary Language.” Department of Computer Science and Information Systems, University of Limerick, 1998.
John R. Koza, “Genetic Programming: A Paradigm for Genetically Breeding Populations of Computer Programs to Solve Problems”, Computer Science Department, Stanford University, Jun. 1990.
John R. Koza, “Hierarchical Genetic Algorithms Operating on Populations of Computer Programs”, Computer Science Department, Stanford University, 1989.
Candida Ferreira, “Gene Expressing Programming: A New Adaptive Algorithm for Solving Problems”, Complex Systems, vol. 13, issue 2:87-129, 2001.
P.A. Whigham, “Inductive Bias and Genetic Programming”, “First International Conference on Genetic Algorithms in Engineering Systems: Innovations and Applications, {GALESIA}”, vol. 414, 12-14, pp. 461-466, IEE, Sheffield, UK, 1995.
Rafal Salustowicz and Jürgen Schmidhuber, “Probabilistic Incremental Program Evolution” “Evolutionary Computation”, 5 (2): 123-141, 1997.

LandOfFree

Say what you really think

Search LandOfFree.com for the USA inventors and patents. Rate them and share your experience with other people.

Rating

Generative programming system and method employing focused... does not yet have a rating. At this time, there are no reviews or comments for this patent.

If you have personal experience with Generative programming system and method employing focused..., we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Generative programming system and method employing focused... will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFUS-PAI-O-4096525

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.