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Danger invariants

Abstract:

Static analysers search for overapproximating proofs of safety commonly known as safety invariants. Conversely, static bug finders (e.g. Bounded Model Checking) give evidence for the failure of an assertion in the form of a counterexample trace. As opposed to safety invariants, the size of a counterexample is dependent on the depth of the bug, i.e., the length of the execution trace prior to the error state, which also determines the computational effort required to find them. We propose a way of expressing danger proofs that is independent of the depth of bugs. Essentially, such danger proofs constitute a compact representation of a counterexample trace, which we call a danger invariant. Danger invariants summarise sets of traces that are guaranteed to be able to reach an error state. Our conjecture is that such danger proofs will enable the design of bug finding analyses for which the computational effort is independent of the depth of bugs, and thus find deep bugs more efficiently. As an exemplar of an analysis that uses danger invariants, we design a bug finding technique based on a synthesis engine. We implemented this technique and compute danger invariants for intricate programs taken from SV-COMP 2016.

Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1007/978-3-319-48989-6_12

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Institution:
University of Oxford
Division:
MPLS Division
Department:
Computer Science
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS Division
Department:
Computer Science
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Computer Science
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS Division
Department:
Computer Science
Role:
Author

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Role:
Editor
Role:
Editor
Role:
Editor
Role:
Editor


Publisher:
Springer Verlag
Host title:
FM 2016: Formal Methods: 21st International Symposium, Limassol, Cyprus, November 9-11, 2016, Proceedings
Journal:
FM 2016: Formal Methods: 21st International Symposium, Limassol, Cyprus, November 9-11, 2016, Proceedings More from this journal
Pages:
182-198
Series:
Lecture Notes in Computer Science
Publication date:
2016-01-01
Acceptance date:
2016-08-08
DOI:
ISSN:
0302-9743
ISBN:
9783319489889


Pubs id:
pubs:832753
UUID:
uuid:784f5715-195d-407e-bb9e-06ef19ba6932
Local pid:
pubs:832753
Source identifiers:
832753
Deposit date:
2018-05-03
ARK identifier:

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