research-article

Superstate identification for state machines using search-based clustering

Authors:

Phil McMinn, and

Neil WalkinshawAuthors Info & Claims

GECCO '10: Proceedings of the 12th annual conference on Genetic and evolutionary computation

July 2010

Pages 1381 - 1388

https://doi.org/10.1145/1830483.1830736

Published: 07 July 2010 Publication History

Abstract

State machines are a popular method of representing a system at a high level of abstraction that enables developers to gain an overview of the system they represent and quickly understand it.

Several techniques have been developed to reverse engineer state machines from software, so as to produce a concise and up-to-date document of how a system works. However, the machines that are recovered are usually flat and contain a large number of states. This means that the abstract picture they are supposed to provide is often itself very complex, requiring effort to understand.

This paper proposes the use of search-based clustering as a means of overcoming this problem. Clustering state machines opens up the possibility of recovering the structural hierarchy of a state machine, such that superstates may be identified. An evaluation study is performed using the Bunch search-based clustering tool, which demonstrates the usefulness of the approach.

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Cited By

Amtoft TAndroutsopoulos KClark D(2020)Correctly Slicing Extended Finite State MachinesFrom Lambda Calculus to Cybersecurity Through Program Analysis10.1007/978-3-030-41103-9_6(149-197)Online publication date: 15-Feb-2020
https://doi.org/10.1007/978-3-030-41103-9_6
Hall M(2011)Complexity metrics for hierarchical state machinesProceedings of the Third international conference on Search based software engineering10.5555/2042243.2042257(76-81)Online publication date: 10-Sep-2011
https://dl.acm.org/doi/10.5555/2042243.2042257
Hall MGyimóthy TZeller A(2011)Search based hierarchy generation for reverse engineered state machinesProceedings of the 19th ACM SIGSOFT symposium and the 13th European conference on Foundations of software engineering10.1145/2025113.2025170(392-395)Online publication date: 5-Sep-2011
https://dl.acm.org/doi/10.1145/2025113.2025170
Show More Cited By

Index Terms

Superstate identification for state machines using search-based clustering
1. Software and its engineering
  1. Software creation and management
    1. Software post-development issues
      1. Documentation
      2. Software reverse engineering
  2. Software organization and properties
    1. Software system structures
      1. Software system models
        State systems

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cover image ACM Conferences

GECCO '10: Proceedings of the 12th annual conference on Genetic and evolutionary computation

July 2010

1520 pages

ISBN:9781450300728

DOI:10.1145/1830483

General Chair:
Martin Pelikan
University of Missouri, USA
,
Program Chair:
Jürgen Branke
University of Warwick, Coventry, UK

Copyright © 2010 ACM.

Permission to make digital or hard copies of all or part 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 components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGEVO: ACM Special Interest Group on Genetic and Evolutionary Computation

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 07 July 2010

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GECCO '10

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SIGEVO

GECCO '10: Genetic and Evolutionary Computation Conference

July 7 - 11, 2010

Oregon, Portland, USA

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Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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Cited By

Amtoft TAndroutsopoulos KClark D(2020)Correctly Slicing Extended Finite State MachinesFrom Lambda Calculus to Cybersecurity Through Program Analysis10.1007/978-3-030-41103-9_6(149-197)Online publication date: 15-Feb-2020
https://doi.org/10.1007/978-3-030-41103-9_6
Hall M(2011)Complexity metrics for hierarchical state machinesProceedings of the Third international conference on Search based software engineering10.5555/2042243.2042257(76-81)Online publication date: 10-Sep-2011
https://dl.acm.org/doi/10.5555/2042243.2042257
Hall MGyimóthy TZeller A(2011)Search based hierarchy generation for reverse engineered state machinesProceedings of the 19th ACM SIGSOFT symposium and the 13th European conference on Foundations of software engineering10.1145/2025113.2025170(392-395)Online publication date: 5-Sep-2011
https://dl.acm.org/doi/10.1145/2025113.2025170
Hall M(2011)Complexity Metrics for Hierarchical State MachinesSearch Based Software Engineering10.1007/978-3-642-23716-4_10(76-81)Online publication date: 2011
https://doi.org/10.1007/978-3-642-23716-4_10

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