Finding short counterexamples in promela models using estimation of distribution algorithms

Created by W.Langdon from gp-bibliography.bib Revision:1.7615

@InProceedings{Staunton:2011:GECCO,

• author = "Jan Staunton and John A. Clark",
• title = "Finding short counterexamples in promela models using estimation of distribution algorithms",
• booktitle = "GECCO '11: Proceedings of the 13th annual conference on Genetic and evolutionary computation",
• year = "2011",
• editor = "Natalio Krasnogor and Pier Luca Lanzi and Andries Engelbrecht and David Pelta and Carlos Gershenson and Giovanni Squillero and Alex Freitas and Marylyn Ritchie and Mike Preuss and Christian Gagne and Yew Soon Ong and Guenther Raidl and Marcus Gallager and Jose Lozano and Carlos Coello-Coello and Dario Landa Silva and Nikolaus Hansen and Silja Meyer-Nieberg and Jim Smith and Gus Eiben and Ester Bernado-Mansilla and Will Browne and Lee Spector and Tina Yu and Jeff Clune and Greg Hornby and Man-Leung Wong and Pierre Collet and Steve Gustafson and Jean-Paul Watson and Moshe Sipper and Simon Poulding and Gabriela Ochoa and Marc Schoenauer and Carsten Witt and Anne Auger",
• isbn13 = "978-1-4503-0557-0",
• pages = "1923--1930",
• keywords = "genetic algorithms, genetic programming, Search-based software engineering",
• month = "12-16 " # jul,
• organisation = "SIGEVO",
• address = "Dublin, Ireland",
• DOI = "doi:10.1145/2001576.2001834",
• publisher = "ACM",
• publisher_address = "New York, NY, USA",
• abstract = "Model checking is an automatic technique that exhaustively checks the state space of a system/program to prove if a specification is satisfied. If an error is detected, the precise circumstances of the issue are returned to the user in the form of a counterexample. Exhaustively checking the state space of a large system, a system with many concurrent components for example, is often intractable. In this scenario, heuristic mechanisms can be employed with the task of detecting errors rather than proving the system is correct. Recently, a metaheuristic EDA-based approach to detecting deadlock in multithreaded Java software has shown great promise in this area. In this paper, we extend that work to search Promela models for counterexamples. We show that the EDA-based technique can find errors where algorithms such as A* search fail. We also show the ability of the EDA to find shorter errors than those discovered by traditional heuristic methods.",
• notes = "Also known as \cite{2001834} GECCO-2011 A joint meeting of the twentieth international conference on genetic algorithms (ICGA-2011) and the sixteenth annual genetic programming conference (GP-2011)",

}

Genetic Programming entries for Jan Staunton John A Clark

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