A Systematic Literature Review on prioritizing software test cases using Markov chains
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1016/j.infsof.2022.106902 http://hdl.handle.net/11449/223716 |
Resumo: | Context: Software Testing is a costly activity since the size of the test case set tends to increase as the construction of the software evolves. Test Case Prioritization (TCP) can reduce the effort and cost of software testing. TCP is an activity where a subset of the existing test cases is selected in order to maximize the possibility of finding defects. On the other hand, Markov Chains representing a reactive system, when solved, can present the occupation time of each of their states. The idea is to use such information and associate priority to those test cases that consist of states with the highest probabilities. Objective: The objective of this paper is to conduct a survey to identify and understand key initiatives for using Markov Chains in TCP. Aspects such as approaches, developed techniques, programming languages, analytical and simulation results, and validation tests are investigated. Methods: A Systematic Literature Review (SLR) was conducted considering studies published up to July 2021 from five different databases to answer the three research questions. Results: From SLR, we identified 480 studies addressing Markov Chains in TCP that have been reviewed in order to extract relevant information on a set of research questions. Conclusion: The final 12 studies analyzed use Markov Chains at some stage of test case prioritization in a distinct way, that is, we found that there is no strong relationship between any of the studies, not only on how the technique was used but also in the context of the application. Concerning the fields of application of this subject, 6 forms of approach were found: Controlled Markov Chain, Usage Model, Model-Based Test, Regression Test, Statistical Test, and Random Test. This demonstrates the versatility and robustness of the tool. A large part of the studies developed some prioritization tool, being its validation done in some cases analytically and in others numerically, such as: Measure of the software specification, Optimal Test Transition Probabilities, Adaptive Software Testing, Automatic Prioritization, Ant Colony Optimization, Model Driven approach, and Monte Carlo Random Testing. |
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A Systematic Literature Review on prioritizing software test cases using Markov chainsMarkov ChainsSystematic Literature ReviewTest case prioritizationContext: Software Testing is a costly activity since the size of the test case set tends to increase as the construction of the software evolves. Test Case Prioritization (TCP) can reduce the effort and cost of software testing. TCP is an activity where a subset of the existing test cases is selected in order to maximize the possibility of finding defects. On the other hand, Markov Chains representing a reactive system, when solved, can present the occupation time of each of their states. The idea is to use such information and associate priority to those test cases that consist of states with the highest probabilities. Objective: The objective of this paper is to conduct a survey to identify and understand key initiatives for using Markov Chains in TCP. Aspects such as approaches, developed techniques, programming languages, analytical and simulation results, and validation tests are investigated. Methods: A Systematic Literature Review (SLR) was conducted considering studies published up to July 2021 from five different databases to answer the three research questions. Results: From SLR, we identified 480 studies addressing Markov Chains in TCP that have been reviewed in order to extract relevant information on a set of research questions. Conclusion: The final 12 studies analyzed use Markov Chains at some stage of test case prioritization in a distinct way, that is, we found that there is no strong relationship between any of the studies, not only on how the technique was used but also in the context of the application. Concerning the fields of application of this subject, 6 forms of approach were found: Controlled Markov Chain, Usage Model, Model-Based Test, Regression Test, Statistical Test, and Random Test. This demonstrates the versatility and robustness of the tool. A large part of the studies developed some prioritization tool, being its validation done in some cases analytically and in others numerically, such as: Measure of the software specification, Optimal Test Transition Probabilities, Adaptive Software Testing, Automatic Prioritization, Ant Colony Optimization, Model Driven approach, and Monte Carlo Random Testing.Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Universidade Estadual Paulista (UNESP)Universidade Tecnológica Federal do Paraná (UTFPR), Cornélio ProcópioInstituto Federal de Educação Ciência e Tecnologia de São Paulo (IFSP)Instituto Nacional de Pesquisas Espaciais (INPE)Universidade Estadual Paulista (UNESP)CNPq: 432247/2018-1Universidade Estadual Paulista (UNESP)Universidade Tecnológica Federal do Paraná (UTFPR)Ciência e Tecnologia de São Paulo (IFSP)Instituto Nacional de Pesquisas Espaciais (INPE)Barbosa, Gerson [UNESP]de Souza, Érica Ferreirados Santos, Luciana Brasil Rebeloda Silva, MarlonBalera, Juliana MarinoVijaykumar, Nandamudi Lankalapalli2022-04-28T19:52:41Z2022-04-28T19:52:41Z2022-07-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://dx.doi.org/10.1016/j.infsof.2022.106902Information and Software Technology, v. 147.0950-5849http://hdl.handle.net/11449/22371610.1016/j.infsof.2022.1069022-s2.0-85127084991Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengInformation and Software Technologyinfo:eu-repo/semantics/openAccess2022-04-28T19:52:41Zoai:repositorio.unesp.br:11449/223716Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T23:46:17.122309Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
A Systematic Literature Review on prioritizing software test cases using Markov chains |
title |
A Systematic Literature Review on prioritizing software test cases using Markov chains |
spellingShingle |
A Systematic Literature Review on prioritizing software test cases using Markov chains Barbosa, Gerson [UNESP] Markov Chains Systematic Literature Review Test case prioritization |
title_short |
A Systematic Literature Review on prioritizing software test cases using Markov chains |
title_full |
A Systematic Literature Review on prioritizing software test cases using Markov chains |
title_fullStr |
A Systematic Literature Review on prioritizing software test cases using Markov chains |
title_full_unstemmed |
A Systematic Literature Review on prioritizing software test cases using Markov chains |
title_sort |
A Systematic Literature Review on prioritizing software test cases using Markov chains |
author |
Barbosa, Gerson [UNESP] |
author_facet |
Barbosa, Gerson [UNESP] de Souza, Érica Ferreira dos Santos, Luciana Brasil Rebelo da Silva, Marlon Balera, Juliana Marino Vijaykumar, Nandamudi Lankalapalli |
author_role |
author |
author2 |
de Souza, Érica Ferreira dos Santos, Luciana Brasil Rebelo da Silva, Marlon Balera, Juliana Marino Vijaykumar, Nandamudi Lankalapalli |
author2_role |
author author author author author |
dc.contributor.none.fl_str_mv |
Universidade Estadual Paulista (UNESP) Universidade Tecnológica Federal do Paraná (UTFPR) Ciência e Tecnologia de São Paulo (IFSP) Instituto Nacional de Pesquisas Espaciais (INPE) |
dc.contributor.author.fl_str_mv |
Barbosa, Gerson [UNESP] de Souza, Érica Ferreira dos Santos, Luciana Brasil Rebelo da Silva, Marlon Balera, Juliana Marino Vijaykumar, Nandamudi Lankalapalli |
dc.subject.por.fl_str_mv |
Markov Chains Systematic Literature Review Test case prioritization |
topic |
Markov Chains Systematic Literature Review Test case prioritization |
description |
Context: Software Testing is a costly activity since the size of the test case set tends to increase as the construction of the software evolves. Test Case Prioritization (TCP) can reduce the effort and cost of software testing. TCP is an activity where a subset of the existing test cases is selected in order to maximize the possibility of finding defects. On the other hand, Markov Chains representing a reactive system, when solved, can present the occupation time of each of their states. The idea is to use such information and associate priority to those test cases that consist of states with the highest probabilities. Objective: The objective of this paper is to conduct a survey to identify and understand key initiatives for using Markov Chains in TCP. Aspects such as approaches, developed techniques, programming languages, analytical and simulation results, and validation tests are investigated. Methods: A Systematic Literature Review (SLR) was conducted considering studies published up to July 2021 from five different databases to answer the three research questions. Results: From SLR, we identified 480 studies addressing Markov Chains in TCP that have been reviewed in order to extract relevant information on a set of research questions. Conclusion: The final 12 studies analyzed use Markov Chains at some stage of test case prioritization in a distinct way, that is, we found that there is no strong relationship between any of the studies, not only on how the technique was used but also in the context of the application. Concerning the fields of application of this subject, 6 forms of approach were found: Controlled Markov Chain, Usage Model, Model-Based Test, Regression Test, Statistical Test, and Random Test. This demonstrates the versatility and robustness of the tool. A large part of the studies developed some prioritization tool, being its validation done in some cases analytically and in others numerically, such as: Measure of the software specification, Optimal Test Transition Probabilities, Adaptive Software Testing, Automatic Prioritization, Ant Colony Optimization, Model Driven approach, and Monte Carlo Random Testing. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-04-28T19:52:41Z 2022-04-28T19:52:41Z 2022-07-01 |
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://dx.doi.org/10.1016/j.infsof.2022.106902 Information and Software Technology, v. 147. 0950-5849 http://hdl.handle.net/11449/223716 10.1016/j.infsof.2022.106902 2-s2.0-85127084991 |
url |
http://dx.doi.org/10.1016/j.infsof.2022.106902 http://hdl.handle.net/11449/223716 |
identifier_str_mv |
Information and Software Technology, v. 147. 0950-5849 10.1016/j.infsof.2022.106902 2-s2.0-85127084991 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Information and Software Technology |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.source.none.fl_str_mv |
Scopus reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
_version_ |
1808129549564641280 |