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muPRL: A Mutation Testing Pipeline for Deep Reinforcement Learning based on Real Faults

Fuente: arXiv

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Dettagli Bibliografici
Autori principali:	Thomas, Deepak-George, Biagiola, Matteo, Humbatova, Nargiz, Wardat, Mohammad, Jahangirova, Gunel, Rajan, Hridesh, Tonella, Paolo
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Software Engineering
Accesso online:	Acceder al recurso
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