A “more intelligent” test case generation approach through task models manipulation
Autor(a) principal: | |
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Data de Publicação: | 2017 |
Outros Autores: | , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/1822/51052 |
Resumo: | Ensuring that an interactive application allows users to perform their activities and reach their goals is critical to the overall usability of the interactive application. Indeed, the effectiveness factor of usability directly refers to this capability. Assessing effectiveness is a real challenge for usability testing as usability tests only cover a very limited number of tasks and activities. This paper proposes an approach towards automated testing of effectiveness of interactive applications. To this end we resort to two main elements: an exhaustive description of users’ activities and goals using task models, and the generation of scenarios (from the task models) to be tested over the application. However, the number of scenarios can be very high (beyond the computing capabilities of machines) and we might end up testing multiple similar scenarios. In order to overcome these problems, we propose strategies based on task models manipulations (e.g., manipulating task nodes, operator nodes, information ...) resulting in a more intelligent test case generation approach. For each strategy, we investigate its relevance (both in terms of test case generation and in terms of validity compared to the original task models) and we illustrate it with a small example. Finally, the proposed strategies are applied on a real-size case study demonstrating their relevance and validity to test interactive applications. |
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A “more intelligent” test case generation approach through task models manipulationCiências Naturais::Ciências da Computação e da InformaçãoEngenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e InformáticaEnsuring that an interactive application allows users to perform their activities and reach their goals is critical to the overall usability of the interactive application. Indeed, the effectiveness factor of usability directly refers to this capability. Assessing effectiveness is a real challenge for usability testing as usability tests only cover a very limited number of tasks and activities. This paper proposes an approach towards automated testing of effectiveness of interactive applications. To this end we resort to two main elements: an exhaustive description of users’ activities and goals using task models, and the generation of scenarios (from the task models) to be tested over the application. However, the number of scenarios can be very high (beyond the computing capabilities of machines) and we might end up testing multiple similar scenarios. In order to overcome these problems, we propose strategies based on task models manipulations (e.g., manipulating task nodes, operator nodes, information ...) resulting in a more intelligent test case generation approach. For each strategy, we investigate its relevance (both in terms of test case generation and in terms of validity compared to the original task models) and we illustrate it with a small example. Finally, the proposed strategies are applied on a real-size case study demonstrating their relevance and validity to test interactive applications.Work at HASLab was carried out in the context of project "NORTE-01-0145-FEDER-000016", financed by the North Portugal Regional Operational Programme (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement, and through the European Regional Development Fund (ERDF).info:eu-repo/semantics/publishedVersionAssociation for Computing Machinery (ACM)Universidade do MinhoCampos, José C.Fayollas, CamilleGonçalves, MarceloMartinie, CéliaNavarre, DavidPalanque, PhilippePinto, Miguel20172017-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/1822/51052eng2573-014210.1145/3095811info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-07-21T12:19:44Zoai:repositorium.sdum.uminho.pt:1822/51052Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T19:12:42.254618Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
A “more intelligent” test case generation approach through task models manipulation |
title |
A “more intelligent” test case generation approach through task models manipulation |
spellingShingle |
A “more intelligent” test case generation approach through task models manipulation Campos, José C. Ciências Naturais::Ciências da Computação e da Informação Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática |
title_short |
A “more intelligent” test case generation approach through task models manipulation |
title_full |
A “more intelligent” test case generation approach through task models manipulation |
title_fullStr |
A “more intelligent” test case generation approach through task models manipulation |
title_full_unstemmed |
A “more intelligent” test case generation approach through task models manipulation |
title_sort |
A “more intelligent” test case generation approach through task models manipulation |
author |
Campos, José C. |
author_facet |
Campos, José C. Fayollas, Camille Gonçalves, Marcelo Martinie, Célia Navarre, David Palanque, Philippe Pinto, Miguel |
author_role |
author |
author2 |
Fayollas, Camille Gonçalves, Marcelo Martinie, Célia Navarre, David Palanque, Philippe Pinto, Miguel |
author2_role |
author author author author author author |
dc.contributor.none.fl_str_mv |
Universidade do Minho |
dc.contributor.author.fl_str_mv |
Campos, José C. Fayollas, Camille Gonçalves, Marcelo Martinie, Célia Navarre, David Palanque, Philippe Pinto, Miguel |
dc.subject.por.fl_str_mv |
Ciências Naturais::Ciências da Computação e da Informação Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática |
topic |
Ciências Naturais::Ciências da Computação e da Informação Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática |
description |
Ensuring that an interactive application allows users to perform their activities and reach their goals is critical to the overall usability of the interactive application. Indeed, the effectiveness factor of usability directly refers to this capability. Assessing effectiveness is a real challenge for usability testing as usability tests only cover a very limited number of tasks and activities. This paper proposes an approach towards automated testing of effectiveness of interactive applications. To this end we resort to two main elements: an exhaustive description of users’ activities and goals using task models, and the generation of scenarios (from the task models) to be tested over the application. However, the number of scenarios can be very high (beyond the computing capabilities of machines) and we might end up testing multiple similar scenarios. In order to overcome these problems, we propose strategies based on task models manipulations (e.g., manipulating task nodes, operator nodes, information ...) resulting in a more intelligent test case generation approach. For each strategy, we investigate its relevance (both in terms of test case generation and in terms of validity compared to the original task models) and we illustrate it with a small example. Finally, the proposed strategies are applied on a real-size case study demonstrating their relevance and validity to test interactive applications. |
publishDate |
2017 |
dc.date.none.fl_str_mv |
2017 2017-01-01T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/1822/51052 |
url |
http://hdl.handle.net/1822/51052 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
2573-0142 10.1145/3095811 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Association for Computing Machinery (ACM) |
publisher.none.fl_str_mv |
Association for Computing Machinery (ACM) |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
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1799132563371982848 |