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


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2019-02

AUTHORS

Zhiyi Zhang, Xiaoyuan Xie

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. More... »

PAGES

123-125

References to SciGraph publications

Journal

TITLE

Biophysical Reviews

ISSUE

1

VOLUME

11

Author Affiliations

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s12551-018-0492-6

DOI

http://dx.doi.org/10.1007/s12551-018-0492-6

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1110757434

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/30565204


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