Guiding the Search Towards Failure-Inducing Test Inputs Using Support Vector Machines

Author:

Sorokin Lev1ORCID,Kerscher Niklas2ORCID

Affiliation:

1. fortiss GmbH, Munich, Germany

2. Technische Universität München, Munich, Germany

Funder

HORIZON EUROPE Framework Programme

Publisher

ACM

Reference35 articles.

1. Shaukat Ali et al. "Quality Indicators in Search-Based Software Engineering: An Empirical Evaluation". In: ACM Trans. Softw. Eng. Methodol. (2020).

2. Andrea Arcuri and Lionel Briand. "A Hitchhiker's guide to statistical tests for assessing randomized algorithms in software engineering". In: Softw. Test. Verif. Reliab. (2014), pp. 219--250.

3. Raja Ben Abdessalem et al. "Testing Advanced Driver Assistance Systems Using Multi-Objective Search and Neural Networks". In: ASE. 2016, 63--74.

4. Testing autonomous cars for feature interaction failures using many-objective search

5. Testing vision-based control systems using learnable evolutionary algorithms

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