A semantic mutation metric for metamorphic relation adequacy in scientific computing programs

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Main Author: Li, Meng
Format: Recurso digital
Published: Zenodo 2026
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author Li, Meng
author_facet Li, Meng
contents Metamorphic Testing addresses the test-oracle problem in scientific computing, but classical Mutation Score (MS) operates on syntactic AST mutations and misses domain semantics. We propose the Semantic Mutation Score (SMS), built on five domain-semantic operators (Conservation Erosion, Operator Substitution, Hyperparameter, Trajectory Flip, Structural Injection). SMS degenerates almost everywhere to MS in a characterised limit, preserving backward compatibility with the classical mutation-testing lineage. A 12-PUT x 5-MP design over four single-output float-to-float classes (numeric, probabilistic, surrogate, ML) is paired with a three-layer attribution classifier separating true semantic faults from tolerance, OOD, statistical, and artefact categories. The pre-registered large-effect threshold for Cliff's delta is not met under the point-estimate criterion; the observed effect lies in the medium-effect range. Cross-source pooling under an identical prompt does not appreciably shift delta. AST-level overlap between LLM-generated and default cosmic-ray syntactic mutants is small; the Hyperparameter, Structural Injection, and Trajectory Flip classes are unreachable under default first-order syntactic configurations.
format Recurso digital
id zenodo_https___doi_org_10_5281_zenodo_20250665
institution Zenodo
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publishDate 2026
publisher Zenodo
record_format zenodo
spellingShingle A semantic mutation metric for metamorphic relation adequacy in scientific computing programs
Li, Meng
metamorphic testing
mutation testing
semantic mutation operators
metamorphic relation adequacy
LLM-generated mutants
Cliff's delta
scientific computing kernels
Metamorphic Testing addresses the test-oracle problem in scientific computing, but classical Mutation Score (MS) operates on syntactic AST mutations and misses domain semantics. We propose the Semantic Mutation Score (SMS), built on five domain-semantic operators (Conservation Erosion, Operator Substitution, Hyperparameter, Trajectory Flip, Structural Injection). SMS degenerates almost everywhere to MS in a characterised limit, preserving backward compatibility with the classical mutation-testing lineage. A 12-PUT x 5-MP design over four single-output float-to-float classes (numeric, probabilistic, surrogate, ML) is paired with a three-layer attribution classifier separating true semantic faults from tolerance, OOD, statistical, and artefact categories. The pre-registered large-effect threshold for Cliff's delta is not met under the point-estimate criterion; the observed effect lies in the medium-effect range. Cross-source pooling under an identical prompt does not appreciably shift delta. AST-level overlap between LLM-generated and default cosmic-ray syntactic mutants is small; the Hyperparameter, Structural Injection, and Trajectory Flip classes are unreachable under default first-order syntactic configurations.
title A semantic mutation metric for metamorphic relation adequacy in scientific computing programs
topic metamorphic testing
mutation testing
semantic mutation operators
metamorphic relation adequacy
LLM-generated mutants
Cliff's delta
scientific computing kernels
url https://doi.org/10.5281/zenodo.20250665