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Inferring automata-based programs from specification with mutation-based ant colony optimization

Published: 12 July 2014 Publication History

Abstract

In this paper we address the problem of constructing correct-by-design programs with the use of the automata-based programming paradigm. A recent algorithm for learning finite-state machines (FSMs) MuACOsm is applied to the problem of inferring extended finite-state machine (EFSM) models from behavior examples (test scenarios) and temporal properties, and is shown to outperform the genetic algorithm (GA) used earlier.

Supplementary Material

ZIP File (pap388.zip)
1. cd to src/gabp and execute: ant && ./deploy 2. cd to src/muaco and execute: ant && ant -f build-jar.xml && ./deploy

References

[1]
T. Back, D. B. Fogel, and Z. Michalewicz, editors. Handbook of Evolutionary Computation. IOP Publishing Ltd., Bristol, UK, UK, 1st edition, 1997.
[2]
D. Chivilikhin and V. Ulyantsev. MuACOsm: A New Mutation-Based Ant Colony Optimization Algorithm for Learning Finite-State Machines. In Proceedings of the fifteenth annual conference on Genetic and evolutionary computation, GECCO '13, pages 511--518, New York, NY, USA, 2013. ACM.
[3]
E. M. Clarke, O. Grumberg, and D. A. Peled. Model checking. MIT press, 1999.
[4]
V. Levenshtein. Binary Codes Capable of Correcting Deletions, Insertions and Reversals. Soviet Physics Doklady, 10:707, 1966.
[5]
M. López-Ibáñez, J. Dubois-Lacoste, T. Stützle, and M. Birattari. The irace package, Iterated Race for Automatic Algorithm Configuration. Technical Report TR/IRIDIA/2011-004, IRIDIA, Universitè Libre de Bruxelles, Belgium, 2011.
[6]
A. Shalyto and N. Tukkel'. SWITCH Technology: An Automated Approach to Developing Software for Reactive Systems. Programming and Computer Software, 27(5):260--276, 2001.
[7]
F. Tsarev and K. Egorov. Finite State Machine Induction Using Genetic Algorithm Based on Testing and Model Checking. In Proceedings of the 13th Annual Conference Companion on Genetic and Evolutionary Computation, GECCO '11, pages 759--762, New York, NY, USA, 2011. ACM.
[8]
F. Wilcoxon. Individual Comparisons by Ranking Methods. Biometrics Bulletin, 1(6):80--83, Dec. 1945.

Cited By

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  • (2019)Exploring the Relationship between the Structural and the Actual Similarities of AutomataProceedings of the 3rd International Conference on Machine Learning and Soft Computing10.1145/3310986.3311032(81-86)Online publication date: 25-Jan-2019
  • (2017)Neural network for synthesizing deterministic finite automataProcedia Computer Science10.1016/j.procs.2017.11.162119:C(73-82)Online publication date: 1-Dec-2017
  • (2016)Modified ant colony algorithm for constructing finite state machines from execution scenarios and temporal formulasAutomation and Remote Control10.1134/S000511791603009777:3(473-484)Online publication date: 1-Mar-2016
  • Show More Cited By

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Published In

cover image ACM Conferences
GECCO Comp '14: Proceedings of the Companion Publication of the 2014 Annual Conference on Genetic and Evolutionary Computation
July 2014
1524 pages
ISBN:9781450328814
DOI:10.1145/2598394
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 12 July 2014

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Author Tags

  1. design/synthesis
  2. empirical study
  3. software engineering

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GECCO '14
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GECCO '14: Genetic and Evolutionary Computation Conference
July 12 - 16, 2014
BC, Vancouver, Canada

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GECCO Comp '14 Paper Acceptance Rate 180 of 544 submissions, 33%;
Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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Cited By

View all
  • (2019)Exploring the Relationship between the Structural and the Actual Similarities of AutomataProceedings of the 3rd International Conference on Machine Learning and Soft Computing10.1145/3310986.3311032(81-86)Online publication date: 25-Jan-2019
  • (2017)Neural network for synthesizing deterministic finite automataProcedia Computer Science10.1016/j.procs.2017.11.162119:C(73-82)Online publication date: 1-Dec-2017
  • (2016)Modified ant colony algorithm for constructing finite state machines from execution scenarios and temporal formulasAutomation and Remote Control10.1134/S000511791603009777:3(473-484)Online publication date: 1-Mar-2016
  • (2014)Combining Exact and Metaheuristic Techniques for Learning Extended Finite-State Machines from Test Scenarios and Temporal PropertiesProceedings of the 2014 13th International Conference on Machine Learning and Applications10.1109/ICMLA.2014.62(350-355)Online publication date: 3-Dec-2014

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