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Implementation-level verification of algorithms with KeY

Authors: Daniel Bruns; Wojciech Mostowski; Mattias Ulbrich;

Implementation-level verification of algorithms with KeY

Abstract

We give an account on the authors' experience and results from the software verification competition held at the Formal Methods 2012 conference. Competitions like this are meant to provide a benchmark for verification systems. It consisted of three algorithms which the authors have implemented in Java, specified with the Java Modeling Language, and verified using the KeY system. Building on our solutions, we argue that verification systems which target implementations in real-world programming languages are required to have powerful capabilities for abstraction. Regarding the KeY tool, we explain features which, driven by the competition, have been freshly implemented to accommodate for these demands.

Countries
Netherlands, Germany
Related Organizations
Keywords

ddc:004, theorem prover, Theorem prover, DATA processing & computer science, Benchmark, 004, Formal verification, benchmark, Java Modeling Language, formal verification, info:eu-repo/classification/ddc/004, Java modeling language

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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    9
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
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    Top 10%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
9
Average
Average
Top 10%
Green
bronze