Statistical Analysis for Revealing Defects in Software Projects: Systematic Literature Review

Bibliographic Details
Main Author: Mahmoud, Alia Nabil
Publication Date: 2021
Other Authors: Santos, Vítor
Format: Other
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: http://hdl.handle.net/10362/128665
Summary: Mahmoud, A. N., & Santos, V. (2021). Statistical Analysis for Revealing Defects in Software Projects: Systematic Literature Review. International Journal of Advanced Computer Science and Applications, 12(11), 237-249. https://doi.org/10.14569/IJACSA.2021.0121128
id RCAP_e83681ebd56ee1f6d854bd148bbbc48b
oai_identifier_str oai:run.unl.pt:10362/128665
network_acronym_str RCAP
network_name_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository_id_str https://opendoar.ac.uk/repository/7160
spelling Statistical Analysis for Revealing Defects in Software Projects: Systematic Literature ReviewDefectsSoftware projectsStatistical modelLinear regressionLogistic regressionComputer Science(all)SDG 9 - Industry, Innovation, and InfrastructureMahmoud, A. N., & Santos, V. (2021). Statistical Analysis for Revealing Defects in Software Projects: Systematic Literature Review. International Journal of Advanced Computer Science and Applications, 12(11), 237-249. https://doi.org/10.14569/IJACSA.2021.0121128Defect detection in software is the procedure to identify parts of software that may comprise defects. Software companies always seek to improve the performance of software projects in terms of quality and efficiency. They also seek to deliver the soft-ware projects without any defects to the communities and just in time. The early revelation of defects in software projects is also tried to avoid failure of those projects, save costs, team effort, and time. Therefore, these companies need to build an intelligent model capable of detecting software defects accurately and efficiently. The paper is organized as follows. Section 2 presents the materials and methods, PRISMA, search questions, and search strategy. Section 3 presents the results with an analysis, and discussion, visualizing analysis and analysis per topic. Section 4 presents the methodology. Finally, in Section 5, the conclusion is discussed. The search string was applied to all electronic repositories looking for papers published between 2015 and 2021, which resulted in 627 publications. The results focused on finding three important points by linking the results of manuscript analysis and linking them to the results of the bibliometric analysis. First, the results showed that the number of defects and the number of lines of code are among the most important factors used in revealing software defects. Second, neural networks and regression analysis are among the most important smart and statistical methods used for this purpose. Finally, the accuracy metric and the error rate are among the most important metrics used in comparisons between the efficiency of statistical and intelligent models.NOVA Information Management School (NOVA IMS)Information Management Research Center (MagIC) - NOVA Information Management SchoolRUNMahmoud, Alia NabilSantos, Vítor2021-12-03T23:48:28Z2021-11-302021-11-30T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/other13application/pdfhttp://hdl.handle.net/10362/128665eng2158-107XPURE: 35181543https://doi.org/10.14569/IJACSA.2021.0121128info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-05-22T17:57:24Zoai:run.unl.pt:10362/128665Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T17:28:21.050051Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Statistical Analysis for Revealing Defects in Software Projects: Systematic Literature Review
title Statistical Analysis for Revealing Defects in Software Projects: Systematic Literature Review
spellingShingle Statistical Analysis for Revealing Defects in Software Projects: Systematic Literature Review
Mahmoud, Alia Nabil
Defects
Software projects
Statistical model
Linear regression
Logistic regression
Computer Science(all)
SDG 9 - Industry, Innovation, and Infrastructure
title_short Statistical Analysis for Revealing Defects in Software Projects: Systematic Literature Review
title_full Statistical Analysis for Revealing Defects in Software Projects: Systematic Literature Review
title_fullStr Statistical Analysis for Revealing Defects in Software Projects: Systematic Literature Review
title_full_unstemmed Statistical Analysis for Revealing Defects in Software Projects: Systematic Literature Review
title_sort Statistical Analysis for Revealing Defects in Software Projects: Systematic Literature Review
author Mahmoud, Alia Nabil
author_facet Mahmoud, Alia Nabil
Santos, Vítor
author_role author
author2 Santos, Vítor
author2_role 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
Santos, Vítor
dc.subject.por.fl_str_mv Defects
Software projects
Statistical model
Linear regression
Logistic regression
Computer Science(all)
SDG 9 - Industry, Innovation, and Infrastructure
topic Defects
Software projects
Statistical model
Linear regression
Logistic regression
Computer Science(all)
SDG 9 - Industry, Innovation, and Infrastructure
description Mahmoud, A. N., & Santos, V. (2021). Statistical Analysis for Revealing Defects in Software Projects: Systematic Literature Review. International Journal of Advanced Computer Science and Applications, 12(11), 237-249. https://doi.org/10.14569/IJACSA.2021.0121128
publishDate 2021
dc.date.none.fl_str_mv 2021-12-03T23:48:28Z
2021-11-30
2021-11-30T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/other
format other
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/128665
url http://hdl.handle.net/10362/128665
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 2158-107X
PURE: 35181543
https://doi.org/10.14569/IJACSA.2021.0121128
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:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron:RCAAP
instname_str FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron_str RCAAP
institution RCAAP
reponame_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
collection Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository.name.fl_str_mv Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
repository.mail.fl_str_mv info@rcaap.pt
_version_ 1833596719924772864

Similar Items