Towards Agentic Test-Driven Quality Assurance for 6G Networks
On the map: LLM agents and tool use → Software engineering coding agents
Abstract (arXiv)
This work proposes an agentic, intent-driven end-to-end (E2E) orchestration framework that integrates intent co-creation with a Test-Driven Quality Assurance paradigm. In this framework, autonomous agents iteratively refine a user's initial intent into a confirmed, auditable specification. Furthermore, the system automatically derives validation tests from these intents before provisioning, directly mirroring the Test-Driven Development workflow in software engineering to ensure proactive Service Level Agreement (SLA) compliance. The architecture is grounded in a standards-aligned knowledge representation using TM Forum (TMF) information models and catalogs. This enables deterministic graph traversal from high-level Product Offerings down to granular Service/Resource and Test specifications. We prototyped this architecture by extending OpenSlice with a message-driven, multi-agent pattern and integrating MCP-enabled (Model Context Protocol) tool access for real-time knowledge retrieval. Currently, our evaluation of the agents targets the intent co-creation phase as a baseline toward full-scale orchestration. Building on experiments with multiple open-source Large Language Model (LLM) backends integrated with the TMF-based knowledge base, we observe substantial variability in tool-use reliability and hallucination patterns, underscoring the critical importance of robust knowledge integration in agentic 6G systems.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Placed in Software engineering coding agents, one of 16 directions in LLM agents and tool use. Builds on 3 of its 27 references that are in the map. First posted on arXiv 25 Apr 2026.
Builds on
3 of 27 references.
References · 3
- 2025Advanced Architectures Integrated with Agentic AI for Next-Generation Wireless Networkscited by 11
- 2025A Reference Architecture for Autonomous Networks: An Agent-Based Approachcited by 3
- 2025SANNet: A Semantic-Aware Agentic AI Networking Framework for Multi-Agent Cross-Layer Coordinationcited by 3
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- 2025An Empirical Study of Testing Practices in Open Source AI Agent Frameworks and Agentic Applications
- 2026Tool Forge: A Validation-Carrying Toolchain for Governed Agentic Execution