A Proposed Model for Detecting Defects in Software Projects

Detalhes bibliográficos
Autor(a) principal: Mahmoud, Alia Nabil
Data de Publicação: 2024
Outros Autores: Abdelaziz, Ahmed, Santos, Vítor, Freire, Mário M.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/162649
Resumo: Mahmoud, A. N., Abdelaziz, A., Santos, V., & Freire, M. M. (2024). A Proposed Model for Detecting Defects in Software Projects. Indonesian Journal of Electrical Engineering and Computer Science, 33(1), 290-302. https://doi.org/10.11591/ijeecs.v33.i1.pp290-302
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spelling A Proposed Model for Detecting Defects in Software ProjectsDefectsLinear regressionLogistic regressionSoftware projectsStatistical modelSignal ProcessingInformation SystemsHardware and ArchitectureComputer Networks and CommunicationsControl and OptimizationElectrical and Electronic EngineeringSDG 9 - Industry, Innovation, and InfrastructureMahmoud, A. N., Abdelaziz, A., Santos, V., & Freire, M. M. (2024). A Proposed Model for Detecting Defects in Software Projects. Indonesian Journal of Electrical Engineering and Computer Science, 33(1), 290-302. https://doi.org/10.11591/ijeecs.v33.i1.pp290-302Defective modules that cause software execution failures are common in large software projects. Source code for a significant number of modules may be found in several software repositories. This software repository includes each module’s software metrics and the module’s faulty status. Software companies face a considerable problem detecting defects in sizeable and complex programming code. In addition, many international reports, such as the comprehensive human appraisal for originating (CHAOS) report, have mentioned that there are countless reasons for the failure of software projects, including the inability to detect errors and defects in the programming code of those projects at an early stage. This research employs a statistical analysis technique to reveal the characteristics that indicate the faulty status of software modules. It is recommended that statistical analysis models derived from the retrieved information be merged with existing project metrics and bug data to improve prediction. When all algorithms are merged with weighted votes, the results indicate enhanced prediction abilities. The proposed statistical analysis outperforms the state-of-the-art method (association rule, decision tree, Naive Bayes, and neural network) in terms of accuracy by 9.1%, 10.3%, 13.1%, and 13.1%, respectively.NOVA Information Management School (NOVA IMS)Information Management Research Center (MagIC) - NOVA Information Management SchoolRUNMahmoud, Alia NabilAbdelaziz, AhmedSantos, VítorFreire, Mário M.2024-01-22T22:53:58Z2024-012024-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article13application/pdfhttp://hdl.handle.net/10362/162649eng2502-4752PURE: 79252619https://doi.org/10.11591/ijeecs.v33.i1.pp290-302info: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:RCAAP2024-03-11T05:45:34Zoai:run.unl.pt:10362/162649Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:59:00.166969Repositório 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 Proposed Model for Detecting Defects in Software Projects
title A Proposed Model for Detecting Defects in Software Projects
spellingShingle A Proposed Model for Detecting Defects in Software Projects
Mahmoud, Alia Nabil
Defects
Linear regression
Logistic regression
Software projects
Statistical model
Signal Processing
Information Systems
Hardware and Architecture
Computer Networks and Communications
Control and Optimization
Electrical and Electronic Engineering
SDG 9 - Industry, Innovation, and Infrastructure
title_short A Proposed Model for Detecting Defects in Software Projects
title_full A Proposed Model for Detecting Defects in Software Projects
title_fullStr A Proposed Model for Detecting Defects in Software Projects
title_full_unstemmed A Proposed Model for Detecting Defects in Software Projects
title_sort A Proposed Model for Detecting Defects in Software Projects
author Mahmoud, Alia Nabil
author_facet Mahmoud, Alia Nabil
Abdelaziz, Ahmed
Santos, Vítor
Freire, Mário M.
author_role author
author2 Abdelaziz, Ahmed
Santos, Vítor
Freire, Mário M.
author2_role author
author
author
dc.contributor.none.fl_str_mv NOVA Information Management School (NOVA IMS)
Information Management Research Center (MagIC) - NOVA Information Management School
RUN
dc.contributor.author.fl_str_mv Mahmoud, Alia Nabil
Abdelaziz, Ahmed
Santos, Vítor
Freire, Mário M.
dc.subject.por.fl_str_mv Defects
Linear regression
Logistic regression
Software projects
Statistical model
Signal Processing
Information Systems
Hardware and Architecture
Computer Networks and Communications
Control and Optimization
Electrical and Electronic Engineering
SDG 9 - Industry, Innovation, and Infrastructure
topic Defects
Linear regression
Logistic regression
Software projects
Statistical model
Signal Processing
Information Systems
Hardware and Architecture
Computer Networks and Communications
Control and Optimization
Electrical and Electronic Engineering
SDG 9 - Industry, Innovation, and Infrastructure
description Mahmoud, A. N., Abdelaziz, A., Santos, V., & Freire, M. M. (2024). A Proposed Model for Detecting Defects in Software Projects. Indonesian Journal of Electrical Engineering and Computer Science, 33(1), 290-302. https://doi.org/10.11591/ijeecs.v33.i1.pp290-302
publishDate 2024
dc.date.none.fl_str_mv 2024-01-22T22:53:58Z
2024-01
2024-01-01T00:00:00Z
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/10362/162649
url http://hdl.handle.net/10362/162649
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 2502-4752
PURE: 79252619
https://doi.org/10.11591/ijeecs.v33.i1.pp290-302
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 13
application/pdf
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
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str 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
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