mlsanityData to 14 Oct 2026

Agentic RAG for Software Testing with Hybrid Vector-Graph and Multi-Agent Orchestration

arXiv 2510.10824 ↗First posted 12 Oct 2025cs.SE cs.AIcited by 2

On the map: Retrieval-augmented generation → Agentic RAG, agents and memory

also in 1 more
Abstract (arXiv)

We present an approach to software testing automation using Agentic Retrieval-Augmented Generation (RAG) systems for Quality Engineering (QE) artifact creation. We combine autonomous AI agents with hybrid vector-graph knowledge systems to automate test plan, case, and QE metric generation. Our approach addresses traditional software testing limitations by leveraging LLMs such as Gemini and Mistral, multi-agent orchestration, and enhanced contextualization. The system achieves remarkable accuracy improvements from 65% to 94.8% while ensuring comprehensive document traceability throughout the quality engineering lifecycle. Experimental validation of enterprise Corporate Systems Engineering and SAP migration projects demonstrates an 85% reduction in testing timeline, an 85% improvement in test suite efficiency, and projected 35% cost savings, resulting in a 2-month acceleration of go-live.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Placed in Agentic RAG, agents and memory, one of 15 directions in Retrieval-augmented generation. Builds on 8 of its 29 references that are in the map. First posted on arXiv 12 Oct 2025.

Builds on

8 of 29 references.

References · 8

  1. 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,297
  2. 2022ReAct: Synergizing Reasoning and Acting in Language Modelscited by 8,695
  3. 2023Toolformer: Language Models Can Teach Themselves to Use Toolscited by 4,182
  4. 2020Dense Passage Retrieval for Open-Domain Question Answeringcited by 3,824
  5. 2023Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflectioncited by 1,839
  6. 2020Leveraging Passage Retrieval with Generative Models for Open Domain Question Answeringcited by 1,210
  7. 2025Semantic Mastery: Enhancing LLMs with Advanced Natural Language Understandingcited by 4
  8. 2025Enhancing Software Quality Assurance with an Adaptive Differential Evolution based Quantum Variational Autoencoder-Transformer Modelcited by 1

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 1; 2026: 1.

2 papers.

  1. 2025Reinforcement Learning Integrated Agentic RAG for Software Test Cases Authoringcited by 0
  2. 2026Assistance to Autonomy: A Systematic Literature Review of Agentic AI across the Software Development Life Cyclecited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2026The Rise of Agentic Testing: Multi-Agent Systems for Robust Software Quality Assurance
  2. 2026Supporting software engineering tasks with agentic AI: Demonstration on document retrieval and test scenario generation
  3. 2026Grounding AI Agents in Contracts: An Empirical Evaluation of Spec-Driven Test Generation
  4. 2026AINTMA: Agentic AI Architecture for Autonomous Test Management with Generative Intelligence, Secure Cloud Communication and Adaptive Quality Analytics
  5. 2026Beyond Test Presence: Assessing the Quality and Robustness of Agent-Generated Tests in Open-Source Projects
  6. 2024Agentic AI-Driven Technical Troubleshooting for Enterprise Systems: A Novel Weighted Retrieval-Augmented Generation Paradigm
  7. 2026Agent-Based Test Assertion Generation via Diverse Perspective Aggregation
  8. 2026AI Assurance: A Comprehensive Testing Strategy for Enterprise AI Systems