An Extended Abstract of "Metamorphic Testing: Testing the Untestable"

Segura, Sergio; Towey, Dave; Zhi, Zhou; Chen, Tsong Yueh

doi:10.1109/compsac.2019.00037

Cited by 3 publications

(2 citation statements)

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“…It has seen an increase adoption in research and real-world applications. Comprehensive surveys of metamorphic testing may be found in [5,6,7,8,9,10].…”

Section: Introductionmentioning

confidence: 99%

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Towards Automated Metamorphic Test Identification for Ocean System Models

Hiremath¹,

Claus²,

Hasselbring³

et al. 2021

Preprint

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Metamorphic testing seeks to verify software in the absence of test oracles. Our application domain is ocean system modeling, where test oracles rarely exist, but where symmetries of the simulated physical systems are known. The input data set is large owing to the requirements of the application domain.This paper presents work in progress for the automated generation of metamorphic test scenarios using machine learning. We extended our previously proposed method [1] to identify metamorphic relations with reduced computational complexity. Initially, we represent metamorphic relations as identity maps. We construct a cost function that minimizes for identifying a metamorphic relation orthogonal to previously found metamorphic relations and penalize for the identity map. A machine learning algorithm is used to identify all possible metamorphic relations minimizing the defined cost function. We propose applying dimensionality reduction techniques to identify attributes in the input which have high variance among the identified metamorphic relations. We apply mutation on these selected attributes to identify distinct metamorphic relations with reduced computational complexity. For experimental evaluation, we subject the two implementations of an ocean-modeling application to the proposed method to present the use of metamorphic relations to test the two implementations of this application.

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“…It has seen an increase adoption in research and real-world applications. Comprehensive surveys of metamorphic testing may be found in [5,6,7,8,9,10].…”

Section: Introductionmentioning

confidence: 99%

“…MT is not without its limitations. A major limit is that MT by itself cannot prove that the output of the application is correct [8]. It is also challenging to quantify the effectiveness of MT.…”

Section: Introductionmentioning

confidence: 99%