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Automated Detection of Logical Errors in Programs

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Risks and Security of Internet and Systems (CRiSIS 2014)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8924))

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Abstract

Static and dynamic program analysis tools mostly focus on the detection of a priori defined defect patterns and security vulnerabilities. Automated detection of logical errors, due to a faulty implementation of applications’ functionality is a relatively uncharted territory. Automation can be based on profiling the intended behavior behind the source code. In this paper, we present a new code profiling method that combines the crosschecking of dynamic program invariants with symbolic execution, an information flow analysis, and the use of fuzzy logic. Our goal is to detect logical errors and exploitable vulnerabilities. The theoretical underpinnings and the practical implementation of our approach are discussed. We test the APP_LogGIC tool that implements the proposed analysis on two real-world applications. The results show that profiling the intended program behavior is feasible in diverse applications. We discuss the heuristics used to overcome the problem of state space explosion and of the large data sets. Code metrics and test results are provided to demonstrate the effectiveness of the approach.

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Acknowledgment

This research has been co-financed by the European Union (European Social Fund ESF) and Greek national funds through the Operational Program “Education and Lifelong Learning” of the National Strategic Reference Framework (NSRF) - Research Funding Program: Thalis Athens University of Economics and Business - Software Engineering Research Platform.

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Authors and Affiliations

  1. Information Security and Critical Infrastructure Protection Laboratory, Department of Informatics, Athens University of Economics and Business (AUEB), Athens, Greece

    George Stergiopoulos & Dimitris Gritzalis

  2. Department of Informatics, Aristotle University of Thessaloniki, Thessaloniki, Greece

    Panagiotis Katsaros

Authors
  1. George Stergiopoulos
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  2. Panagiotis Katsaros
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  3. Dimitris Gritzalis
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Corresponding author

Correspondence to Panagiotis Katsaros .

Editor information

Editors and Affiliations

  1. University of Málaga, Malaga, Spain

    Javier Lopez

  2. Colorado State University, Fort Collins, Colorado, USA

    Indrajit Ray

  3. University of Trento, Trento, Italy

    Bruno Crispo

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Stergiopoulos, G., Katsaros, P., Gritzalis, D. (2015). Automated Detection of Logical Errors in Programs. In: Lopez, J., Ray, I., Crispo, B. (eds) Risks and Security of Internet and Systems. CRiSIS 2014. Lecture Notes in Computer Science(), vol 8924. Springer, Cham. https://doi.org/10.1007/978-3-319-17127-2_3

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  • DOI: https://doi.org/10.1007/978-3-319-17127-2_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-17126-5

  • Online ISBN: 978-3-319-17127-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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