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Main Authors: Duque-Torres, Alejandra, Pfahl, Dietmar, Klammer, Claus, Fischer, Stefan
Format: Preprint
Published: 2023
Subjects:
Online Access:https://arxiv.org/abs/2307.15522
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author Duque-Torres, Alejandra
Pfahl, Dietmar
Klammer, Claus
Fischer, Stefan
author_facet Duque-Torres, Alejandra
Pfahl, Dietmar
Klammer, Claus
Fischer, Stefan
contents Identifying and selecting high-quality Metamorphic Relations (MRs) is a challenge in Metamorphic Testing (MT). While some techniques for automatically selecting MRs have been proposed, they are either domain-specific or rely on strict assumptions about the applicability of a pre-defined MRs. This paper presents a preliminary evaluation of MetaTrimmer, a method for selecting and constraining MRs based on test data. MetaTrimmer comprises three steps: generating random test data inputs for the SUT (Step 1), performing test data transformations and logging MR violations (Step 2), and conducting manual inspections to derive constraints (Step 3). The novelty of MetaTrimmer is its avoidance of complex prediction models that require labeled datasets regarding the applicability of MRs. Moreover, MetaTrimmer facilitates the seamless integration of MT with advanced fuzzing for test data generation. In a preliminary evaluation, MetaTrimmer shows the potential to overcome existing limitations and enhance MR effectiveness.
format Preprint
id arxiv_https___arxiv_org_abs_2307_15522
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Exploring a Test Data-Driven Method for Selecting and Constraining Metamorphic Relations
Duque-Torres, Alejandra
Pfahl, Dietmar
Klammer, Claus
Fischer, Stefan
Software Engineering
D.2
Identifying and selecting high-quality Metamorphic Relations (MRs) is a challenge in Metamorphic Testing (MT). While some techniques for automatically selecting MRs have been proposed, they are either domain-specific or rely on strict assumptions about the applicability of a pre-defined MRs. This paper presents a preliminary evaluation of MetaTrimmer, a method for selecting and constraining MRs based on test data. MetaTrimmer comprises three steps: generating random test data inputs for the SUT (Step 1), performing test data transformations and logging MR violations (Step 2), and conducting manual inspections to derive constraints (Step 3). The novelty of MetaTrimmer is its avoidance of complex prediction models that require labeled datasets regarding the applicability of MRs. Moreover, MetaTrimmer facilitates the seamless integration of MT with advanced fuzzing for test data generation. In a preliminary evaluation, MetaTrimmer shows the potential to overcome existing limitations and enhance MR effectiveness.
title Exploring a Test Data-Driven Method for Selecting and Constraining Metamorphic Relations
topic Software Engineering
D.2
url https://arxiv.org/abs/2307.15522