Metamorphic relation automation: Rationale, challenges, and solution directions

<p dir="ltr">Metamorphic testing addresses the issue of the oracle problem by comparing results transformation from multiple test executions. The relationship that governs the output transformation is called metamorphic relation. Metamorphic relations require expert knowledge and the...

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محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Emran Altamimi (21397883) (author)
مؤلفون آخرون: Abdullah Elkawakjy (21397886) (author), Cagatay Catal (6897842) (author)
منشور في: 2022
الموضوعات:
الوسوم: إضافة وسم
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author Emran Altamimi (21397883)
author2 Abdullah Elkawakjy (21397886)
Cagatay Catal (6897842)
author2_role author
author
author_facet Emran Altamimi (21397883)
Abdullah Elkawakjy (21397886)
Cagatay Catal (6897842)
author_role author
dc.creator.none.fl_str_mv Emran Altamimi (21397883)
Abdullah Elkawakjy (21397886)
Cagatay Catal (6897842)
dc.date.none.fl_str_mv 2022-09-15T09:00:00Z
dc.identifier.none.fl_str_mv 10.1002/smr.2509
dc.relation.none.fl_str_mv https://figshare.com/articles/journal_contribution/Metamorphic_relation_automation_Rationale_challenges_and_solution_directions/29116892
dc.rights.none.fl_str_mv CC BY 4.0
info:eu-repo/semantics/openAccess
dc.subject.none.fl_str_mv Information and computing sciences
Machine learning
Software engineering
automation
machine learning
metamorphic relations
metamorphic testing
dc.title.none.fl_str_mv Metamorphic relation automation: Rationale, challenges, and solution directions
dc.type.none.fl_str_mv Text
Journal contribution
info:eu-repo/semantics/publishedVersion
text
contribution to journal
description <p dir="ltr">Metamorphic testing addresses the issue of the oracle problem by comparing results transformation from multiple test executions. The relationship that governs the output transformation is called metamorphic relation. Metamorphic relations require expert knowledge and the generation of them is considered a time‐consuming task. Researchers have proposed various techniques to automate metamorphic testing, generation, and selection. Although there are several research articles on this issue, there is a lack of overview of the state‐of‐the‐art of metamorphic relation automation. As such, we performed a systematic literature review study to collect, extract, and synthesize the required data. Based on our research questions, the literature was categorized and summarized into different categories. We found that the automation of metamorphic relation is most effective in mathematical and scientific applications. We concluded that some approaches involve analysis of different forms of software‐related information such as control flow graph and program dependence graph as well as an initial set of metamorphic relations. On the other hand, other methods involve analysis of executions of the software functions with random and specific inputs. The results show that this field is still in its infancy with opportunities for novel work, especially in methods utilizing machine learning.</p><h2>Other Information</h2><p dir="ltr">Published in: Journal of Software: Evolution and Process<br>License: <a href="http://creativecommons.org/licenses/by/4.0/" target="_blank">http://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1002/smr.2509" target="_blank">https://dx.doi.org/10.1002/smr.2509</a></p>
eu_rights_str_mv openAccess
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identifier_str_mv 10.1002/smr.2509
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spelling Metamorphic relation automation: Rationale, challenges, and solution directionsEmran Altamimi (21397883)Abdullah Elkawakjy (21397886)Cagatay Catal (6897842)Information and computing sciencesMachine learningSoftware engineeringautomationmachine learningmetamorphic relationsmetamorphic testing<p dir="ltr">Metamorphic testing addresses the issue of the oracle problem by comparing results transformation from multiple test executions. The relationship that governs the output transformation is called metamorphic relation. Metamorphic relations require expert knowledge and the generation of them is considered a time‐consuming task. Researchers have proposed various techniques to automate metamorphic testing, generation, and selection. Although there are several research articles on this issue, there is a lack of overview of the state‐of‐the‐art of metamorphic relation automation. As such, we performed a systematic literature review study to collect, extract, and synthesize the required data. Based on our research questions, the literature was categorized and summarized into different categories. We found that the automation of metamorphic relation is most effective in mathematical and scientific applications. We concluded that some approaches involve analysis of different forms of software‐related information such as control flow graph and program dependence graph as well as an initial set of metamorphic relations. On the other hand, other methods involve analysis of executions of the software functions with random and specific inputs. The results show that this field is still in its infancy with opportunities for novel work, especially in methods utilizing machine learning.</p><h2>Other Information</h2><p dir="ltr">Published in: Journal of Software: Evolution and Process<br>License: <a href="http://creativecommons.org/licenses/by/4.0/" target="_blank">http://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1002/smr.2509" target="_blank">https://dx.doi.org/10.1002/smr.2509</a></p>2022-09-15T09:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.1002/smr.2509https://figshare.com/articles/journal_contribution/Metamorphic_relation_automation_Rationale_challenges_and_solution_directions/29116892CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/291168922022-09-15T09:00:00Z
spellingShingle Metamorphic relation automation: Rationale, challenges, and solution directions
Emran Altamimi (21397883)
Information and computing sciences
Machine learning
Software engineering
automation
machine learning
metamorphic relations
metamorphic testing
status_str publishedVersion
title Metamorphic relation automation: Rationale, challenges, and solution directions
title_full Metamorphic relation automation: Rationale, challenges, and solution directions
title_fullStr Metamorphic relation automation: Rationale, challenges, and solution directions
title_full_unstemmed Metamorphic relation automation: Rationale, challenges, and solution directions
title_short Metamorphic relation automation: Rationale, challenges, and solution directions
title_sort Metamorphic relation automation: Rationale, challenges, and solution directions
topic Information and computing sciences
Machine learning
Software engineering
automation
machine learning
metamorphic relations
metamorphic testing