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arXiv · 2608.15491

HxAgent: Iterative Agent Planning for End-to-End Web Application Testing

Tu Nguyen·Duy Cao·Viet Nguyen·Phu Nguyen·Vy Le·Nguyen TK Nguyen·Tien N. Nguyen·Vu Nguyen
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Abstract

In automated web testing, generating test cases and performing testing using functionality descriptions in natural-language is crucial for improving efficacy. These tasks require such a testing agent to carry out tasks on the target application and generating tests autonomously. We introduce HxAgent, an iterative LLM-based planning agent with a proactive correction strategy. After each step, HxAgent reassesses the web state to determine the next action using (1) current observations, (2) short-term memory of past actions, and (3) long-term experience extracted from past (in)correct sequences of actions. HxAgent achieves 97.4% Exact-Match accuracy on MiniWoB++, comparable to the best baselines without human demonstrations and surpassing the recent WALT by 10.5%. On a dataset of 350 web tasks, it attains 83.8% Exact-Match and 91.8% Prefix-Match, exceeding WALT by 13.4%. On OnlineMind2Web, it further improves over WALT by 4.6%.

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Tu Nguyen, Duy Cao, Viet Nguyen, Phu Nguyen, Vy Le, Nguyen TK Nguyen, Tien N. Nguyen, Vu Nguyen. 2026-08-16. HxAgent: Iterative Agent Planning for End-to-End Web Application Testing. https://arxiv.org/abs/2608.15491

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