Can Cooperative Multi-Agent Reinforcement Learning Boost Automatic Web Testing? An Exploratory Study

Reinforcement learning (RL)-based web GUI testing techniques have attracted significant attention in both academia and industry due to their ability to facilitate automatic and intelligent exploration of websites under test. Yet, the existing approaches that leverage a single RL agent often struggle...

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Vydané v:	IEEE/ACM International Conference on Automated Software Engineering : [proceedings] s. 14 - 26
Hlavní autori:	Fan, Yujia, Wang, Sinan, Fei, Zebang, Qin, Yao, Li, Huaxuan, Liu, Yepang
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	ACM 27.10.2024
Predmet:	Automatic GUI Testing Distributed databases Graphical user interfaces Heuristic algorithms Industries Information Sharing Multi-Agent Reinforcement Learning Periodic structures Reinforcement learning Software engineering Testing Web Testing
ISSN:	2643-1572
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