WebMAC: A Multi-Agent Collaborative Framework for Scenario Testing of Web Systems
Zhenyu Wan, Gong Chen, Qing Huang, Xiaoyuan Xie
TLDR
WebMAC is a multi-agent framework that enhances web system scenario testing by clarifying descriptions and transforming scenarios for improved error detection.
Key contributions
- Introduces WebMAC, a multi-agent framework for robust web system scenario testing.
- Completes test scenario descriptions via interactive clarification with LLMs.
- Transforms scenarios using equivalence class partitioning for improved test adequacy.
- Achieves 30-60% higher script success, 29% efficiency, and 47.6% less token use than SOTA.
Why it matters
This paper addresses critical limitations in LLM-based web scenario testing, which often suffer from incomplete descriptions and inadequate test coverage. WebMAC's multi-agent approach significantly improves testing efficiency and error detection, making web systems more reliable. It also reduces token consumption.
Original Abstract
Scenario testing is an important technique for detecting errors in web systems. Testers draft test scenarios and convert them into test scripts for execution. Early methods relied on testers to convert test scenarios into test scripts. Recent LLM-based scenario testing methods can generate test scripts from natural language descriptions of test scenarios. However, these methods are not only limited by the incompleteness of descriptions but also overlook test adequacy criteria, making it difficult to detect potential errors. To address these limitations, this paper proposes WebMAC, a multi-agent collaborative framework for scenario testing of web systems. WebMAC can complete natural language descriptions of test scenarios through interactive clarification and transform adequate instantiated test scenarios via equivalence class partitioning. WebMAC consists of three multi-agent modules, responsible respectively for completing natural language descriptions of test scenarios, transforming test scenarios, and converting test scripts. We evaluated WebMAC on four web systems. Compared with the SOTA method, WebMAC improves the execution success rate of generated test scripts by 30%-60%, increases testing efficiency by 29%, and reduces token consumption by 47.6%. Furthermore, WebMAC can effectively detect more errors in web systems.
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