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Context-free grammar induction using genetic programming

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A. SpragueAuthors Info & Claims

ACMSE '04: Proceedings of the 42nd annual ACM Southeast Conference

Pages 404 - 405

https://doi.org/10.1145/986537.986635

Published: 02 April 2004 Publication History

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Abstract

While grammar inference is used in areas like natural language acquisition, syntactic pattern recognition, etc., its application to the programming language problem domain has been limited. We propose a new application area for grammar induction which intends to make domain-specific language development easier and finds a second application in renovation tools for legacy systems. The genetic programming approach is used for grammatical inference. Our earlier work used grammar-specific heuristic operators in tandem with non-random construction of the initial grammar population and succeeded in inducing small grammars.

References

[1]

Langdon, W. B., Genetic Programming and Data Structures: Genetic Programming + Data Structures = Automatic Programming!, Kluwer Academic Publishers, 1998.

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[2]

Henriques, P., Varanda Pereira, M., Mernik, M., Lenič, M., Avdičaušević, Žumer, V., Automatic generation of Language based Tools, Electronic Notes in Theoretical Computer Science, Vol. 65 No. 3, Elsevier Science Publisher, 2002.

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[3]

Wyard, P., Representational Issues for Context-Free Grammar Induction Using Genetic Algorithm In Proceedings of the 2nd International Colloquim on Grammatical Inference and Applications, Springer-Verlag Lecture Notes in Artificial Intelligence, Vol 862, pp. 222--235, 1994.

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[4]

Mernik, M., Gerlič, G., Žumer, V., Bryant, B., Can a Parser be Generated from examples?, Proceedings of the ACM Symposium on Applied Computing, pp 1063--1067, 2003.

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[5]

Mernik, M., Lenič, M., Avdičaušević, E., Žumer, V., LISA: An Interactive Environment for Programming Language Development, Proceedings of the 11th International Conference on Compiler Construction, CC'2002, Springer-Verlag Lecture Notes in Computer Science, Vol. 2304, pp. 1--4, 2002.

Digital Library

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[6]

Mernik, M., Črepinšek, M., Gerlič, G., Žumer, V., Bryant, B. R., Sprague, A., Learning Context-Free Grammars using an Evolutionary Approach, submitted for publication

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[7]

Aho, A. V., Sethi., R., Ullman., J. D., Compilers: Principles, Techniques, and Tools, Addison-Wesley, 1986.

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Cited By

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Kalita PSingal DAgarwal PJhunjhunwala SRoy S(2023)Symbolic encoding of LL(1) parsing and its applicationsFormal Methods in System Design10.1007/s10703-023-00420-361:2-3(338-379)Online publication date: 22-Jun-2023
https://dl.acm.org/doi/10.1007/s10703-023-00420-3
Slivnik BKovačević ŽMernik MKosar T(2022)On Comprehension of Genetic Programming Solutions: A Controlled Experiment on Semantic InferenceMathematics10.3390/math1018338610:18(3386)Online publication date: 18-Sep-2022
https://doi.org/10.3390/math10183386
Kovačević ŽMernik MRavber MČrepinšek M(2020)From Grammar Inference to Semantic Inference—An Evolutionary ApproachMathematics10.3390/math80508168:5(816)Online publication date: 18-May-2020
https://doi.org/10.3390/math8050816
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Index Terms

Context-free grammar induction using genetic programming
1. Software and its engineering
  1. Software notations and tools
    1. Compilers

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Published In

ACMSE '04: Proceedings of the 42nd annual ACM Southeast Conference

April 2004

485 pages

ISBN:1581138709

DOI:10.1145/986537

General Chair:
Seong-Moo Yoo
The University of Alabama in Huntsville, Huntsville, AL
,
Program Chair:
Letha Hughes Etzkorn
The University of Alabama in Huntsville, Huntsville, AL

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Association for Computing Machinery

New York, NY, United States

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Published: 02 April 2004

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ACM SE04: ACM Southeast Regional Conference 2004

April 2 - 3, 2004

Alabama, Huntsville

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Overall Acceptance Rate 502 of 1,023 submissions, 49%

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Kalita PSingal DAgarwal PJhunjhunwala SRoy S(2023)Symbolic encoding of LL(1) parsing and its applicationsFormal Methods in System Design10.1007/s10703-023-00420-361:2-3(338-379)Online publication date: 22-Jun-2023
https://dl.acm.org/doi/10.1007/s10703-023-00420-3
Slivnik BKovačević ŽMernik MKosar T(2022)On Comprehension of Genetic Programming Solutions: A Controlled Experiment on Semantic InferenceMathematics10.3390/math1018338610:18(3386)Online publication date: 18-Sep-2022
https://doi.org/10.3390/math10183386
Kovačević ŽMernik MRavber MČrepinšek M(2020)From Grammar Inference to Semantic Inference—An Evolutionary ApproachMathematics10.3390/math80508168:5(816)Online publication date: 18-May-2020
https://doi.org/10.3390/math8050816
Lamela Seijas PThompson SFrancisco M(2018)Model extraction and test generation from JUnit test suitesSoftware Quality Journal10.1007/s11219-017-9399-x26:4(1519-1552)Online publication date: 1-Dec-2018
https://dl.acm.org/doi/10.1007/s11219-017-9399-x
Pandey HChaudhary AMehrotra DKendall G(2016)Maintaining regularity and generalization in data using the minimum description length principle and genetic algorithm: Case of grammatical inferenceSwarm and Evolutionary Computation10.1016/j.swevo.2016.05.00231(11-23)Online publication date: Dec-2016
https://doi.org/10.1016/j.swevo.2016.05.002
Pandey HChaudhary AMehrotra D(2016)Grammar induction using bit masking oriented genetic algorithm and comparative analysisApplied Soft Computing10.1016/j.asoc.2015.09.04438:C(453-468)Online publication date: 1-Jan-2016
https://dl.acm.org/doi/10.1016/j.asoc.2015.09.044
Li SLee D(2015)Learning daily activity patterns with probabilistic grammarsTransportation10.1007/s11116-015-9622-144:1(49-68)Online publication date: 19-May-2015
https://doi.org/10.1007/s11116-015-9622-1
Saha DNarula VBahulkar AKesavasamy KPrabhakar TShroff G(2011)GraminProceedings of the 4th India Software Engineering Conference10.1145/1953355.1953380(185-194)Online publication date: 24-Feb-2011
https://dl.acm.org/doi/10.1145/1953355.1953380
Choubey NKharat M(2010)PDA Simulator for CFG Induction Using Genetic AlgorithmProceedings of the 2010 12th International Conference on Computer Modelling and Simulation10.1109/UKSIM.2010.25(92-97)Online publication date: 24-Mar-2010
https://dl.acm.org/doi/10.1109/UKSIM.2010.25
Pandey H(2010)Context free grammar induction library using Genetic Algorithms2010 International Conference on Computer and Communication Technology (ICCCT)10.1109/ICCCT.2010.5640442(752-758)Online publication date: Sep-2010
https://doi.org/10.1109/ICCCT.2010.5640442
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On restricted context-free grammars

Parsing Arabic using induced probabilistic context free grammar

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Length synchronization context-free grammars

On restricted context-free grammars

Parsing Arabic using induced probabilistic context free grammar

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