{"title":"MUT 模型:表征变质关系多样性的指标","authors":"Xiaodong Xie, Zhehao Li, Jinfu Chen, Yue Zhang, Xiangxiang Wang, Patrick Kwaku Kudjo","doi":"10.1007/s11219-024-09689-x","DOIUrl":null,"url":null,"abstract":"<p>Metamorphic testing emerged as a solution to the Oracle problem, with its foundation deeply rooted in the concept of Metamorphic Relations (MRs). Researchers have made an intriguing discovery that certain diverse MRs exhibit similar fault detection capabilities as the test oracle. However, defining the criteria for diverse MRs has posed a challenge. Traditional metrics like Mutation Score (MS) and Fault Detection Rate (FDR) fail to assess the diversity of MRs. This paper introduces the MUT Model as a foundational framework for analyzing the \"MR Diversity\" between a pair of MRs. The word \"diversity\" in this paper pertains to the differences in the types of faults that two MRs are inclined to detect. The experimental findings indicate that by harnessing posterior knowledge, specifically by analyzing the MUT Model, it is possible to derive prior knowledge that can aid in the construction of Metamorphic Relations. Most importantly, the MUT Model may draw conclusions that violate intuition, exposing more details of the core essence of MR Diversity. Moreover, the concept of MR Diversity serves as a basis for MR selection, resulting in enhanced fault detection capabilities compared to the conventional MS-based approach. Additionally, it offers valuable insights into the construction of composite metamorphic relations, with the goal of amplifying their fault detection abilities beyond those of their individual MR components.</p>","PeriodicalId":21827,"journal":{"name":"Software Quality Journal","volume":"31 1","pages":""},"PeriodicalIF":1.7000,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"MUT Model: a metric for characterizing metamorphic relations diversity\",\"authors\":\"Xiaodong Xie, Zhehao Li, Jinfu Chen, Yue Zhang, Xiangxiang Wang, Patrick Kwaku Kudjo\",\"doi\":\"10.1007/s11219-024-09689-x\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Metamorphic testing emerged as a solution to the Oracle problem, with its foundation deeply rooted in the concept of Metamorphic Relations (MRs). Researchers have made an intriguing discovery that certain diverse MRs exhibit similar fault detection capabilities as the test oracle. However, defining the criteria for diverse MRs has posed a challenge. Traditional metrics like Mutation Score (MS) and Fault Detection Rate (FDR) fail to assess the diversity of MRs. This paper introduces the MUT Model as a foundational framework for analyzing the \\\"MR Diversity\\\" between a pair of MRs. The word \\\"diversity\\\" in this paper pertains to the differences in the types of faults that two MRs are inclined to detect. The experimental findings indicate that by harnessing posterior knowledge, specifically by analyzing the MUT Model, it is possible to derive prior knowledge that can aid in the construction of Metamorphic Relations. Most importantly, the MUT Model may draw conclusions that violate intuition, exposing more details of the core essence of MR Diversity. Moreover, the concept of MR Diversity serves as a basis for MR selection, resulting in enhanced fault detection capabilities compared to the conventional MS-based approach. Additionally, it offers valuable insights into the construction of composite metamorphic relations, with the goal of amplifying their fault detection abilities beyond those of their individual MR components.</p>\",\"PeriodicalId\":21827,\"journal\":{\"name\":\"Software Quality Journal\",\"volume\":\"31 1\",\"pages\":\"\"},\"PeriodicalIF\":1.7000,\"publicationDate\":\"2024-07-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Software Quality Journal\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.1007/s11219-024-09689-x\",\"RegionNum\":3,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"COMPUTER SCIENCE, SOFTWARE ENGINEERING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Software Quality Journal","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1007/s11219-024-09689-x","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, SOFTWARE ENGINEERING","Score":null,"Total":0}
MUT Model: a metric for characterizing metamorphic relations diversity
Metamorphic testing emerged as a solution to the Oracle problem, with its foundation deeply rooted in the concept of Metamorphic Relations (MRs). Researchers have made an intriguing discovery that certain diverse MRs exhibit similar fault detection capabilities as the test oracle. However, defining the criteria for diverse MRs has posed a challenge. Traditional metrics like Mutation Score (MS) and Fault Detection Rate (FDR) fail to assess the diversity of MRs. This paper introduces the MUT Model as a foundational framework for analyzing the "MR Diversity" between a pair of MRs. The word "diversity" in this paper pertains to the differences in the types of faults that two MRs are inclined to detect. The experimental findings indicate that by harnessing posterior knowledge, specifically by analyzing the MUT Model, it is possible to derive prior knowledge that can aid in the construction of Metamorphic Relations. Most importantly, the MUT Model may draw conclusions that violate intuition, exposing more details of the core essence of MR Diversity. Moreover, the concept of MR Diversity serves as a basis for MR selection, resulting in enhanced fault detection capabilities compared to the conventional MS-based approach. Additionally, it offers valuable insights into the construction of composite metamorphic relations, with the goal of amplifying their fault detection abilities beyond those of their individual MR components.
期刊介绍:
The aims of the Software Quality Journal are:
(1) To promote awareness of the crucial role of quality management in the effective construction of the software systems developed, used, and/or maintained by organizations in pursuit of their business objectives.
(2) To provide a forum of the exchange of experiences and information on software quality management and the methods, tools and products used to measure and achieve it.
(3) To provide a vehicle for the publication of academic papers related to all aspects of software quality.
The Journal addresses all aspects of software quality from both a practical and an academic viewpoint. It invites contributions from practitioners and academics, as well as national and international policy and standard making bodies, and sets out to be the definitive international reference source for such information.
The Journal will accept research, technique, case study, survey and tutorial submissions that address quality-related issues including, but not limited to: internal and external quality standards, management of quality within organizations, technical aspects of quality, quality aspects for product vendors, software measurement and metrics, software testing and other quality assurance techniques, total quality management and cultural aspects. Other technical issues with regard to software quality, including: data management, formal methods, safety critical applications, and CASE.