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Transformation-Enabled Precondition Inference

Published online by Cambridge University Press:  23 September 2021

BISHOKSAN KAFLE Open the ORCID record for BISHOKSAN KAFLE [Opens in a new window] ,
GRAEME GANGE ,
PETER J. STUCKEY ,
PETER SCHACHTE  and
HARALD SØNDERGAARD
BISHOKSAN KAFLE
Affiliation:
IMDEA Software Institute, Madrid, Spain (e-mail: bishoksan.kafle@imdea.org)
GRAEME GANGE
Affiliation:
Faculty of IT, Monash University, Clayton Vic. 3800, Australia (e-mails: graeme.gange@monash.edu, peter.stuckey@monash.edu)
PETER J. STUCKEY
Affiliation:
Faculty of IT, Monash University, Clayton Vic. 3800, Australia (e-mails: graeme.gange@monash.edu, peter.stuckey@monash.edu)
PETER SCHACHTE
Affiliation:
School of Computing and Information Systems, The University of Melbourne, Vic. 3010, Australia (e-mails: schachte@unimelb.edu.au, harald@unimelb.edu.au)
HARALD SØNDERGAARD
Affiliation:
School of Computing and Information Systems, The University of Melbourne, Vic. 3010, Australia (e-mails: schachte@unimelb.edu.au, harald@unimelb.edu.au)
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Abstract

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Precondition inference is a non-trivial problem with important applications in program analysis and verification. We present a novel iterative method for automatically deriving preconditions for the safety and unsafety of programs. Each iteration maintains over-approximations of the set of safe and unsafe initial states, which are used to partition the program’s initial states into those known to be safe, known to be unsafe and unknown. We then construct revised programs with those unknown initial states and iterate the procedure until the approximations are disjoint or some termination criteria are met. An experimental evaluation of the method on a set of software verification benchmarks shows that it can infer precise preconditions (sometimes optimal) that are not possible using previous methods.

Keywords

precondition inferenceprogram transformationabstract interpretationoptimal precondition

Information

Type
Original Article
Information
Theory and Practice of Logic Programming , Volume 21 , Special Issue 6: 37th International Conference on Logic Programming Special Issue II , November 2021 , pp. 700 - 716
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Copyright
© The Author(s), 2021. Published by Cambridge University Press

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