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Metadados

1. Identificação
Tipo de ReferênciaArtigo em Evento (Conference Proceedings)
Sitemtc-m16d.sid.inpe.br
Código do Detentorisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identificador8JMKD3MGP7W/397GGFL
Repositóriosid.inpe.br/mtc-m19/2011/02.18.15.03   (acesso restrito)
Última Atualização2011:02.21.15.56.32 (UTC) administrator
Repositório de Metadadossid.inpe.br/mtc-m19/2011/02.18.15.03.54
Última Atualização dos Metadados2021:02.11.18.18.09 (UTC) administrator
Chave SecundáriaINPE--PRE/
DOI10.1109/ICSTW.2010.52
ISBN978-076954050-4
Chave de CitaçãoYanoMartSous:2010:GeFeTe
TítuloGenerating feasible test paths from an executable model using a multi-objective approach
Ano2010
Data de Acesso27 abr. 2024
Tipo SecundárioPRE CI
Número de Arquivos1
Tamanho650 KiB
2. Contextualização
Autor1 Yano, T.
2 Martins, E.
3 Sousa, F. L.
Grupo1
2
3 DMC-ETE-INPE-MCT-BR
Afiliação1 Institute of Computing, State University of Campinas, UNICAMP, Campinas, SP, Brazil
2 Institute of Computing, State University of Campinas, UNICAMP, Campinas, SP, Brazil
3 Instituto Nacional de Pesquisas Espaciais (INPE)
Nome do Evento3rd International Conference on Software Testing, Verification, and Validation Workshops, 3. (ICSTW)
Localização do EventoParis
Data6 - 10 Apr. 2010
VolumeArticle number 5463651
Páginas236-239
Histórico (UTC)2011-02-21 15:56:32 :: marciana -> administrator :: 2010
2021-02-11 18:18:09 :: administrator -> marciana :: 2010
3. Conteúdo e estrutura
É a matriz ou uma cópia?é a matriz
Estágio do Conteúdoconcluido
Transferível1
Tipo do ConteúdoExternal Contribution
Palavras-ChaveExecutable model
Feasible path
Model-based testing
Multi-objective optimization
Behavior model
Evolutionary approach
Executable model
Extended finite state machine
Infeasible paths
Meta heuristics
Multi objective
Open problems
Path models
Size minimization
Test data generation
Test purpose
Test sequence
Testing technique
White-box testing
ResumoSearch-based testing techniques using metaheuristics, like evolutionary algorithms, has been largely used for test data generation, but most approaches were proposed for white-box testing. In this paper we present an evolutionary approach for test sequence generation from a behavior model, in particular, Extended Finite State Machine. An open problem is the production of infeasible paths, as these should be detected and discarded manually. To circumvent this problem, we use an executable model to obtain feasible paths dynamically. An evolutionary algorithm is used to search for solutions that cover a given test purpose, which is a transition of interest. The target transition is used as a criterion to get slicing information, in this way, helping to identify the parts of the model that affect the test purpose. We also present a multi-objective search: the test purpose coverage and the sequence size minimization, as longer sequences require more effort to be executed.
ÁreaETES
ArranjoGenerating feasible test...
Conteúdo da Pasta docacessar
Conteúdo da Pasta sourcenão têm arquivos
Conteúdo da Pasta agreement
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4. Condições de acesso e uso
Idiomaen
Arquivo AlvoYano_Generation.pdf
Grupo de Usuáriosadministrator
marciana
Visibilidadeshown
Permissão de Leituradeny from all and allow from 150.163
Permissão de Atualizaçãonão transferida
5. Fontes relacionadas
Repositório Espelhosid.inpe.br/mtc-m19@80/2009/08.21.17.02.53
Unidades Imediatamente Superiores8JMKD3MGPCW/446AF4B
Acervo Hospedeirosid.inpe.br/mtc-m19@80/2009/08.21.17.02
6. Notas
Campos Vaziosarchivingpolicy archivist booktitle callnumber copyholder copyright creatorhistory descriptionlevel dissemination e-mailaddress edition editor electronicmailaddress format issn label lineage mark nextedition notes numberofvolumes orcid organization parameterlist parentrepositories previousedition previouslowerunit progress project publisher publisheraddress readergroup resumeid rightsholder schedulinginformation secondarydate secondarymark serieseditor session shorttitle sponsor subject tertiarymark tertiarytype type url versiontype
7. Controle da descrição
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