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The Integration of Machine Learning into Automated Test Generation: A Systematic Literature Review. (arXiv:2206.10210v2 [cs.SE] UPDATED)
cs.LG updates on arXiv.org arxiv.org
Context: Machine learning (ML) may enable effective automated test
generation.
Objective: We characterize emerging research, examining testing practices,
researcher goals, ML techniques applied, evaluation, and challenges.
Methods: We perform a systematic literature review on a sample of 97
publications.
Results: ML generates input for system, GUI, unit, performance, and
combinatorial testing or improves the performance of existing generation
methods. ML is also used to generate test verdicts, property-based, and
expected output oracles. Supervised learning - often based on neural networks …
arxiv generation integration learning literature machine machine learning review test