4.6 Article

Metamorphic Relations for Enhancing System Understanding and Use

期刊

IEEE TRANSACTIONS ON SOFTWARE ENGINEERING
卷 46, 期 10, 页码 1120-1154

出版社

IEEE COMPUTER SOC
DOI: 10.1109/TSE.2018.2876433

关键词

Software testing; Information technology; Electronic mail; Software systems; Software maintenance; Metamorphic exploration; symmetry; metamorphic testing; metamorphic relation; metamorphic relation pattern; metamorphic relation input pattern; change direction; oracle problem; user experience; user countermeasure; software validation

资金

  1. Australian Research Council [LP160101691]
  2. Suzhou Insight Cloud Information Technology Co., Ltd.
  3. Artificial Intelligence and Optimisation Research Group of the University of Nottingham Ningbo China
  4. International Doctoral Innovation Centre
  5. Ningbo Education Bureau
  6. Ningbo Science and Technology Bureau
  7. University of Nottingham
  8. Australian Research Council [LP160101691] Funding Source: Australian Research Council

向作者/读者索取更多资源

Modern information technology paradigms, such as online services and off-the-shelf products, often involve a wide variety of users with different or even conflicting objectives. Every software output may satisfy some users, but may also fail to satisfy others. Furthermore, users often do not know the internal working mechanisms of the systems. This situation is quite different from bespoke software, where developers and users typically know each other. This paper proposes an approach to help users to better understand the software that they use, and thereby more easily achieve their objectives-even when they do not fully understand how the system is implemented. Our approach borrows the concept of metamorphic relations from the field of metamorphic testing (MT), using it in an innovative way that extends beyond MT. We also propose a symmetry metamorphic relation pattern and a change direction metamorphic relation input pattern that can be used to derive multiple concrete metamorphic relations. Empirical studies reveal previously unknown failures in some of the most popular applications in the world, and show how our approach can help users to better understand and better use the systems. The empirical results provide strong evidence of the simplicity, applicability, and effectiveness of our methodology.

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