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Biophysical Reviews

, Volume 11, Issue 1, pp 123–125 | Cite as

Towards testing big data analytics software: the essential role of metamorphic testing

  • Zhiyi Zhang
  • Xiaoyuan XieEmail author
Review

Abstract

In the rapidly growing field of big data analysis, scientists from numerous domains such as computer science and biology are constantly challenged by an unprecedented amount of data. While many software programs have been constructed to support processing and analyzing continuous information flow, one under-appreciated challenge in this field is software quality assurance of these big data software platforms. Metamorphic testing, which was proposed to alleviate the oracle problem in the software engineering community, has become an effective approach for software verification and validation. Recent years, we have witnessed successful applications of metamorphic testing in a variety of domains, ranging from bioinformatics to deep learning. In this letter, we review some main applications of metamorphic testing on big data and present visions for the challenges in future research.

Keywords

Software engineering Metamorphic testing Big data software 

Notes

Funding information

This work is supported by National Key R&D Program of China (2018YFB1003901), and the National Natural Science Foundation of China (61572375, 61772263).

Compliance with ethical standards

Conflict of interest

Zhiyi Zhang declares that she has no conflict of interest. Xiaoyuan Xie declares that she has no conflict of interest.

Ethical approval

This article does not contain any studies with human participants or animals performed by any of the authors.

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Copyright information

© International Union for Pure and Applied Biophysics (IUPAB) and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.School of Computer ScienceWuhan UniversityWuhanChina

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