HTML5-based Visualizations to Support Software Fault Isolation

Detalhes bibliográficos
Autor(a) principal: Carlos Miguel de Sousa Gouveia
Data de Publicação: 2013
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: https://repositorio-aberto.up.pt/handle/10216/68519
Resumo: Testing and debugging is the most expensive, error-prone phase in the software development life cycle. Automated software fault localization can drastically improve the efficiency of this phase, thus improving the overall quality of the software. Amongst the most well-known techniques, due to its efficiency and effectiveness, is spectrum-based fault localization. In this project, we propose three HTML5-based dynamic graphical forms to display the diagnostic reports yielded by spectrum-based fault localization. The visualizations proposed, namely Sunburst, Vertical Partition, and Bubble Hierarchy, have been implemented within the GZOLTAR toolset, replacing previous and less-intuitive OpenGL-based visualizations. The GZOLTAR toolset is a plug-and-play plugin for the Eclipse IDE to ease world-wide adoption. Finally, we performed an user study with GZOLTAR and confirmed that the visualizations help to drastically reduce the time needed in debugging (e.g., all participants using the visualizations were able to pinpoint the fault, whereas of those using traditional methods only 35% found the fault). The group that used the visualizations took on average 9 minutes and 17 seconds less than the group that did not use them.
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spelling HTML5-based Visualizations to Support Software Fault IsolationEngenharia electrotécnica, electrónica e informáticaElectrical engineering, Electronic engineering, Information engineeringTesting and debugging is the most expensive, error-prone phase in the software development life cycle. Automated software fault localization can drastically improve the efficiency of this phase, thus improving the overall quality of the software. Amongst the most well-known techniques, due to its efficiency and effectiveness, is spectrum-based fault localization. In this project, we propose three HTML5-based dynamic graphical forms to display the diagnostic reports yielded by spectrum-based fault localization. The visualizations proposed, namely Sunburst, Vertical Partition, and Bubble Hierarchy, have been implemented within the GZOLTAR toolset, replacing previous and less-intuitive OpenGL-based visualizations. The GZOLTAR toolset is a plug-and-play plugin for the Eclipse IDE to ease world-wide adoption. Finally, we performed an user study with GZOLTAR and confirmed that the visualizations help to drastically reduce the time needed in debugging (e.g., all participants using the visualizations were able to pinpoint the fault, whereas of those using traditional methods only 35% found the fault). The group that used the visualizations took on average 9 minutes and 17 seconds less than the group that did not use them.2013-07-102013-07-10T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttps://repositorio-aberto.up.pt/handle/10216/68519engCarlos Miguel de Sousa Gouveiainfo: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:RCAAP2023-11-29T13:21:52Zoai:repositorio-aberto.up.pt:10216/68519Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T23:39:11.980743Repositório 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 HTML5-based Visualizations to Support Software Fault Isolation
title HTML5-based Visualizations to Support Software Fault Isolation
spellingShingle HTML5-based Visualizations to Support Software Fault Isolation
Carlos Miguel de Sousa Gouveia
Engenharia electrotécnica, electrónica e informática
Electrical engineering, Electronic engineering, Information engineering
title_short HTML5-based Visualizations to Support Software Fault Isolation
title_full HTML5-based Visualizations to Support Software Fault Isolation
title_fullStr HTML5-based Visualizations to Support Software Fault Isolation
title_full_unstemmed HTML5-based Visualizations to Support Software Fault Isolation
title_sort HTML5-based Visualizations to Support Software Fault Isolation
author Carlos Miguel de Sousa Gouveia
author_facet Carlos Miguel de Sousa Gouveia
author_role author
dc.contributor.author.fl_str_mv Carlos Miguel de Sousa Gouveia
dc.subject.por.fl_str_mv Engenharia electrotécnica, electrónica e informática
Electrical engineering, Electronic engineering, Information engineering
topic Engenharia electrotécnica, electrónica e informática
Electrical engineering, Electronic engineering, Information engineering
description Testing and debugging is the most expensive, error-prone phase in the software development life cycle. Automated software fault localization can drastically improve the efficiency of this phase, thus improving the overall quality of the software. Amongst the most well-known techniques, due to its efficiency and effectiveness, is spectrum-based fault localization. In this project, we propose three HTML5-based dynamic graphical forms to display the diagnostic reports yielded by spectrum-based fault localization. The visualizations proposed, namely Sunburst, Vertical Partition, and Bubble Hierarchy, have been implemented within the GZOLTAR toolset, replacing previous and less-intuitive OpenGL-based visualizations. The GZOLTAR toolset is a plug-and-play plugin for the Eclipse IDE to ease world-wide adoption. Finally, we performed an user study with GZOLTAR and confirmed that the visualizations help to drastically reduce the time needed in debugging (e.g., all participants using the visualizations were able to pinpoint the fault, whereas of those using traditional methods only 35% found the fault). The group that used the visualizations took on average 9 minutes and 17 seconds less than the group that did not use them.
publishDate 2013
dc.date.none.fl_str_mv 2013-07-10
2013-07-10T00:00:00Z
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