Dynamic Synthesis of Program Invariants using Genetic Programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.7975
- @InProceedings{Cardamone:2011:DSoPIuGP,
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title = "Dynamic Synthesis of Program Invariants using Genetic
Programming",
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author = "Luigi Cardamone and Andrea Mocci and Carlo Ghezzi",
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pages = "617--624",
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booktitle = "Proceedings of the 2011 IEEE Congress on Evolutionary
Computation",
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year = "2011",
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editor = "Alice E. Smith",
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month = "5-8 " # jun,
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address = "New Orleans, USA",
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organization = "IEEE Computational Intelligence Society",
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publisher = "IEEE Press",
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ISBN = "0-7803-8515-2",
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keywords = "genetic algorithms, genetic programming, SBSE,
invariant formula, logic formulae, loop manipulating
array, program comprehension, program in verification,
statement execution, symbolic program manipulation,
transformation rule, iterative methods, program
verification, symbol manipulation",
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URL = "https://www.luigicardamone.it/bibtex.htm",
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URL = "https://www.luigicardamone.it/tesi-pubblicazioni/cardamone2011gp.pdf",
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DOI = "doi:10.1109/CEC.2011.5949677",
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size = "8 pages",
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abstract = "In the field of software engineering, invariant
detection techniques have been proposed to overcome the
problem of software behaviour comprehension. If the
code of a program is available, combining symbolic and
concrete execution has been shown to provide an
effective method to derive logic formulae that describe
a program's behavior. However, symbolic execution does
not work very well with loops, and thus such methods
are not able to derive useful descriptions of programs
containing loops.
we present a preliminary approach that aims to
integrate genetic programming to synthesise a logic
formula that describes the behaviour of a loop. Such
formula could be integrated in a symbolic execution
based approach for invariant detection to synthesize a
complex program behaviour. We present a specific
representation of formulae that works well with loops
manipulating arrays. The technique has been validated
with a set of relevant examples with increasing
complexity. The preliminary results are promising and
show the feasibility of our approach.",
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notes = "CEC2011 sponsored by the IEEE Computational
Intelligence Society, and previously sponsored by the
EPS and the IET.",
- }
Genetic Programming entries for
Luigi Cardamone
Andrea Mocci
Carlo Ghezzi
Citations