From operational to declarative specifications using a genetic algorithm

"In specification-based test generation, sometimes having a formal specification is not sufficient, since the specification may be in a different formalism from that required by the generation approach being used. In this paper, we deal with this problem specifically in the context in which, wh...

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Autores principales: Molina, Facundo, Degiovanni, Renzo, Regis, Germán, Castro, Pablo, Aguirre, Nazareno, Frías, Marcelo
Formato: Ponencias en Congresos acceptedVersion
Lenguaje:Inglés
Publicado: 2019
Materias:
ALGORITMOS GENETICOS
ESTRUCTURA DE DATOS
INVARIANCIA
Acceso en línea:http://ri.itba.edu.ar/handle/123456789/1627
Aporte de:
Repositorio Institucional Instituto Tecnológico de Buenos Aires (ITBA) de Instituto Tecnológico de Buenos Aires (ITBA)
id I32-R138-123456789-1627
record_format dspace
spelling I32-R138-123456789-16272022-12-07T14:13:50Z From operational to declarative specifications using a genetic algorithm Molina, Facundo Degiovanni, Renzo Regis, Germán Castro, Pablo Aguirre, Nazareno Frías, Marcelo ALGORITMOS GENETICOS ESTRUCTURA DE DATOS INVARIANCIA "In specification-based test generation, sometimes having a formal specification is not sufficient, since the specification may be in a different formalism from that required by the generation approach being used. In this paper, we deal with this problem specifically in the context in which, while having a formal specification in the form of an operational invariant written in a sequential programming language, one needs, for test generation, a declarative invariant in a logical formalism. We propose a genetic algorithm that given a catalog of common properties of invariants, such as acyclicity, sortedness and balance, attempts to evolve a conjunction of these that most accurately approximates an original operational specification. We present some details of the algorithm, and an experimental evaluation based on a benchmark of data structures, for which we evolve declarative logical invariants from operational ones." 2019-06-21T17:52:09Z 2019-06-21T17:52:09Z 2018-05 Ponencias en Congresos info:eu-repo/semantics/acceptedVersion 978-1450-35-741-8 0270-5257 http://ri.itba.edu.ar/handle/123456789/1627 en info:eu-repo/semantics/altIdentifier/doi/10.1145/3194718.3194725 application/pdf
institution Instituto Tecnológico de Buenos Aires (ITBA)
institution_str I-32
repository_str R-138
collection Repositorio Institucional Instituto Tecnológico de Buenos Aires (ITBA)
language Inglés
topic ALGORITMOS GENETICOS
ESTRUCTURA DE DATOS
INVARIANCIA
spellingShingle ALGORITMOS GENETICOS
ESTRUCTURA DE DATOS
INVARIANCIA
Molina, Facundo
Degiovanni, Renzo
Regis, Germán
Castro, Pablo
Aguirre, Nazareno
Frías, Marcelo
From operational to declarative specifications using a genetic algorithm
topic_facet ALGORITMOS GENETICOS
ESTRUCTURA DE DATOS
INVARIANCIA
description "In specification-based test generation, sometimes having a formal specification is not sufficient, since the specification may be in a different formalism from that required by the generation approach being used. In this paper, we deal with this problem specifically in the context in which, while having a formal specification in the form of an operational invariant written in a sequential programming language, one needs, for test generation, a declarative invariant in a logical formalism. We propose a genetic algorithm that given a catalog of common properties of invariants, such as acyclicity, sortedness and balance, attempts to evolve a conjunction of these that most accurately approximates an original operational specification. We present some details of the algorithm, and an experimental evaluation based on a benchmark of data structures, for which we evolve declarative logical invariants from operational ones."
format Ponencias en Congresos
acceptedVersion
author Molina, Facundo
Degiovanni, Renzo
Regis, Germán
Castro, Pablo
Aguirre, Nazareno
Frías, Marcelo
author_facet Molina, Facundo
Degiovanni, Renzo
Regis, Germán
Castro, Pablo
Aguirre, Nazareno
Frías, Marcelo
author_sort Molina, Facundo
title From operational to declarative specifications using a genetic algorithm
title_short From operational to declarative specifications using a genetic algorithm
title_full From operational to declarative specifications using a genetic algorithm
title_fullStr From operational to declarative specifications using a genetic algorithm
title_full_unstemmed From operational to declarative specifications using a genetic algorithm
title_sort from operational to declarative specifications using a genetic algorithm
publishDate 2019
url http://ri.itba.edu.ar/handle/123456789/1627
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AT regisgerman fromoperationaltodeclarativespecificationsusingageneticalgorithm
AT castropablo fromoperationaltodeclarativespecificationsusingageneticalgorithm
AT aguirrenazareno fromoperationaltodeclarativespecificationsusingageneticalgorithm
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