MTKeras: An Automated Metamorphic Testing Platform

Yelin Liu, Zhi Quan Zhou, Tsong Yueh Chen, Yang Liu, Dave Towey

Research output: Journal PublicationArticlepeer-review

Abstract

This paper presents an automated, domain-independent, metamorphic testing platform called MTKeras. In this paper, we report on an investigation demonstrating the effectiveness and usability of MTKeras through five case studies in the four domains of image classification, sentiment analysis, search engines and database management systems. We also report on the effectiveness of combining metamorphic relation (input) patterns in individual metamorphic relations, enhancing the failure-finding abilities of the individual relations. The results of our experiments support combining patterns, and the use of MTKeras. The research reported in this paper shows the applicability of metamorphic relation patterns, and introduces a practical tool for the research community.

Original languageEnglish
Pages (from-to)1235-1249
Number of pages15
JournalInternational Journal of Software Engineering and Knowledge Engineering
Volume31
Issue number09
DOIs
Publication statusPublished - 1 Sep 2021

Keywords

  • Keras
  • Metamorphic testing
  • machine learning library
  • metamorphic relation composition
  • metamorphic relation patterns
  • neural network API
  • oracle problem
  • testing tool

ASJC Scopus subject areas

  • Software
  • Computer Networks and Communications
  • Computer Graphics and Computer-Aided Design
  • Artificial Intelligence

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