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Test-Data Generation for Xtext: Tool Paper

Software Language Engineering, p.342-351

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SFLA‐based heuristic method to generate software structural test data

Journal of software : evolution and process, 2020-01, Vol.32 (1), p.n/a

2020

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Test-data generation using genetic algorithms

Software testing, verification & reliability, 1999-12, Vol.9 (4), p.263-282

1999

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Evolutionary algorithms for the multi-objective test data generation problem

Software, practice & experience, 2012-11, Vol.42 (11), p.1331-1362

2012

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A Novel Fitness function of metaheuristic algorithms for test data generation for simulink models based on mutation analysis

The Journal of systems and software, 2016-10, Vol.120, p.17-30

2016

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Bayes-TDG: effective test data generation using Bayesian belief network: toward failure-detection effectiveness and maximum coverage

IET software, 2018-06, Vol.12 (3), p.225-235

2018

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Optimizing compilation with preservation of structural code coverage metrics to support software testing

Software testing, verification & reliability, 2014-05, Vol.24 (3), p.184-218

2014

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Parameter tuning or default values? An empirical investigation in search-based software engineering

Empirical software engineering : an international journal, 2013-06, Vol.18 (3), p.594-623

2013

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Automation of software test data generation using genetic algorithm and reinforcement learning

Expert systems with applications, 2021-11, Vol.183, p.115446, Article 115446

2021

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Automated test-data generation for exception conditions

Software, practice & experience, 2000-01, Vol.30 (1), p.61-79

2000

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An automated test data generation method for void pointers and function pointers in C/C++ libraries and embedded projects

Information and software technology, 2022-05, Vol.145, p.106821, Article 106821

2022

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Set evolution based test data generation for killing stubborn mutants

The Journal of systems and software, 2024-10, Vol.216, p.112121, Article 112121

2024

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A Survey on Data-Flow Testing

ACM computing surveys, 2018-01, Vol.50 (1), p.1-35

2018

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Modified Evolutionary Test Data Generation Algorithm Based on Dynamic Change in Fitness Function Weights

Engineering proceedings, 2023-06, Vol.33 (1), p.23

2023

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Deceiving Humans and Machines Alike: Search-based Test Input Generation for DNNs Using Variational Autoencoders

ACM transactions on software engineering and methodology, 2024-04, Vol.33 (4), p.1-24, Article 103

2024

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COSMOS: A comprehensive framework for automatically generating domain-oriented test suite

Information and software technology, 2023-02, Vol.154, p.107091, Article 107091

2023

Volltextzugriff (PDF)

Orderly Generation of Test Data via Sorting Mutant Branches Based on Their Dominance Degrees for Weak Mutation Testing

IEEE transactions on software engineering, 2022-04, Vol.48 (4), p.1169-1184

2022

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ARTE: Automated Generation of Realistic Test Inputs for Web APIs

IEEE transactions on software engineering, 2023-01, Vol.49 (1), p.348-363

2023

Volltextzugriff (PDF)

Test data generation for covering mutation-based path using MGA for MPI program

The Journal of systems and software, 2024-04, Vol.210, p.111962, Article 111962

2024

Volltextzugriff (PDF)

Integrating an Ensemble Surrogate Model's Estimation into Test Data Generation

IEEE transactions on software engineering, 2022-04, Vol.48 (4), p.1336-1350

2022

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Test Data Generation for Path Coverage of MPI Programs Using SAEO

ACM transactions on software engineering and methodology, 2021-03, Vol.30 (2), p.1-37

2021

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Test Data Generation for Mutation Testing Based on Markov Chain Usage Model and Estimation of Distribution Algorithm

IEEE transactions on software engineering, 2024-03, Vol.50 (3), p.551-573

2024

Volltextzugriff (PDF)

Improving Test Data Generation for MPI Program Path Coverage With FERPSO-IMPR and Surrogate-Assisted Models

IEEE transactions on software engineering, 2024-03, Vol.50 (3), p.495-511

2024

Volltextzugriff (PDF)

MetaSem: metamorphic testing based on semantic information of autonomous driving scenes

Software testing, verification & reliability, 2024-08, Vol.34 (5), p.n/a

2024

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Test-Data Generation for Xtext: Tool Paper

SFLA‐based heuristic method to generate software structural test data

Test-data generation using genetic algorithms

Evolutionary algorithms for the multi-objective test data generation problem

A Novel Fitness function of metaheuristic algorithms for test data generation for simulink models based on mutation analysis

Bayes-TDG: effective test data generation using Bayesian belief network: toward failure-detection effectiveness and maximum coverage

Optimizing compilation with preservation of structural code coverage metrics to support software testing

Parameter tuning or default values? An empirical investigation in search-based software engineering

Automation of software test data generation using genetic algorithm and reinforcement learning

Automated test-data generation for exception conditions

An automated test data generation method for void pointers and function pointers in C/C++ libraries and embedded projects

Set evolution based test data generation for killing stubborn mutants

A Survey on Data-Flow Testing

Modified Evolutionary Test Data Generation Algorithm Based on Dynamic Change in Fitness Function Weights

Deceiving Humans and Machines Alike: Search-based Test Input Generation for DNNs Using Variational Autoencoders

COSMOS: A comprehensive framework for automatically generating domain-oriented test suite

Orderly Generation of Test Data via Sorting Mutant Branches Based on Their Dominance Degrees for Weak Mutation Testing

ARTE: Automated Generation of Realistic Test Inputs for Web APIs

Test data generation for covering mutation-based path using MGA for MPI program

Integrating an Ensemble Surrogate Model's Estimation into Test Data Generation

Test Data Generation for Path Coverage of MPI Programs Using SAEO

Test Data Generation for Mutation Testing Based on Markov Chain Usage Model and Estimation of Distribution Algorithm

Improving Test Data Generation for MPI Program Path Coverage With FERPSO-IMPR and Surrogate-Assisted Models

MetaSem: metamorphic testing based on semantic information of autonomous driving scenes

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