Metamorphic Relation Automation: State of the Art in Detection, Selection, and Generation Over Two Decades

Metamorphic Relation Automation: State of the Art in Detection, Selection, and Generation Over Two Decades | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 24 September 2025 V1 Latest version Share on Metamorphic Relation Automation: State of the Art in Detection, Selection, and Generation Over Two Decades Authors : Zhenqiu Li , Tingting Wu 0000-0003-3588-7839 [email protected] , Dongming Xiang , Mingyue Jiang , Jialing Huang , Zuohua Ding , and Yunwei Dong Authors Info & Affiliations https://doi.org/10.22541/au.175872613.39541241/v1 147 views 164 downloads Contents Abstract Supplementary Material Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract Metamorphic testing (MT) has emerged as a promising technique for alleviating the test oracle problem by determining software behavior through metamorphic relations (MRs) without the need for test oracles. The effectiveness of MT crucially relies on identifying appropriate MRs. The traditional process of identifying MRs required extensive domain knowledge and was labor-intensive. To overcome these limitations, various semi-automation and automation techniques have been proposed, such as metamorphic relation composition, metamorphic relation patterns, etc. Therefore, a systematic organization and synthesis of these techniques, covering principles, applications, evaluations, merits and limitations, and future prospects, remains necessary. Through a comprehensive review of 88 publications on metamorphic relation automation, this paper categorizes the field into three subfields: detection, selection, and generation, and systematically analyzes them in terms of technological evolution, evaluation analysis, as well as challenges and future directions. The technological evolution summarizes the classification, applicability, strengths and weaknesses of all relevant technologies in each subfield. The evaluation analysis includes subject programs, MR expression types, common metrics used to assess the effectiveness of these techniques and fault types that may impact the effectiveness of MR automation. Additionally, the challenges and future directions identify potential areas for further research to address ongoing difficulties within MR automation. This comprehensive review aims to provide a thorough understanding of the current landscape and offer insights for researchers and practitioners in the field of MR automation. Supplementary Material File (manuscript.pdf) Download 330.01 KB Information & Authors Information Version history V1 Version 1 24 September 2025 Copyright This work is licensed under a Non Exclusive No Reuse License. Keywords metamorphic relation detection metamorphic relation generation metamorphic relation selection metamorphic testing oracle problem Authors Affiliations Zhenqiu Li Zhejiang Sci-Tech University View all articles by this author Tingting Wu 0000-0003-3588-7839 [email protected] Zhejiang Sci-Tech University View all articles by this author Dongming Xiang Zhejiang Sci-Tech University View all articles by this author Mingyue Jiang Zhejiang Sci-Tech University View all articles by this author Jialing Huang Zhejiang Sci-Tech University View all articles by this author Zuohua Ding Zhejiang Sci-Tech University View all articles by this author Yunwei Dong Northwestern Polytechnical University View all articles by this author Metrics & Citations Metrics Article Usage 147 views 164 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Zhenqiu Li, Tingting Wu, Dongming Xiang, et al. Metamorphic Relation Automation: State of the Art in Detection, Selection, and Generation Over Two Decades. Authorea . 24 September 2025. DOI: https://doi.org/10.22541/au.175872613.39541241/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download. For more information or tips please see 'Downloading to a citation manager' in the Help menu . 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