Author | Altamimi, Emran |
Author | Elkawakjy, Abdullah |
Author | Catal, Cagatay |
Available date | 2022-11-30T11:23:18Z |
Publication Date | 2022 |
Publication Name | Journal of Software: Evolution and Process |
Resource | Scopus |
Resource | 2-s2.0-85138008319 |
URI | http://dx.doi.org/10.1002/smr.2509 |
URI | http://hdl.handle.net/10576/36774 |
Abstract | 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. 2022 The Authors. Journal of Software: Evolution and Process published by John Wiley & Sons Ltd. |
Sponsor | This publication is supported in part by grant NPRP12C?33905?SP?66 and from the Qatar National Research Fund. The findings achieved herein are solely the responsibility of the authors. Open Access funding provided by the Qatar National Library. |
Language | en |
Publisher | John Wiley and Sons Ltd |
Subject | automation; machine learning; metamorphic relations; metamorphic testing
|
Title | Metamorphic relation automation: Rationale, challenges, and solution directions |
Type | Article Review |
dc.accessType
| Abstract Only |