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FGDM: Reasoning Aware Multi-Agentic Framework for Software Bug Detection using Chain of Thought and Tree of…

By PulseAugur Editorial · [2 sources] ·

Researchers have developed a new framework called FGDM for detecting and repairing software bugs. This multi-agent system leverages Large Language Models (LLMs) with Chain-of-Thought and Tree-of-Thoughts prompting to understand code dependencies. The framework converts code into a flow graph, identifies errors, and generates fixes, integrating with a FAISS vector database for retrieving similar past issues. Experiments on over 100 programs in C and Python showed FGDM outperforming existing methods, significantly reducing Levenshtein distance and improving cosine similarity. AI

IMPACT Introduces a novel multi-agent LLM framework that improves automated software bug detection and repair.

RANK_REASON This is a research paper detailing a novel framework for software bug detection and repair.

Read on arXiv cs.LG →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

FGDM: Reasoning Aware Multi-Agentic Framework for Software Bug Detection using Chain of Thought and Tree of…

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COVERAGE [2]

  1. arXiv cs.LG TIER_1 English(EN) · Srita Padmanabhuni, Bhargavi Karuturi, Jerusha Karen Indupalli, Santhan Reddy Chilla, Vivek Yelleti ·

    FGDM: Reasoning Aware Multi-Agentic Framework for Software Bug Detection using Chain of Thought and Tree of Thought Prompting

    arXiv:2604.24831v1 Announce Type: cross Abstract: Deep Learning methods are becoming prominent in automated software bug detection; however, they lack the global understanding of the given code. Consequently, their performance tends to degrade, especially when they are applied to…

  2. Hugging Face Daily Papers TIER_1 English(EN) ·

    FGDM: Reasoning Aware Multi-Agentic Framework for Software Bug Detection using Chain of Thought and Tree of Thought Prompting

    Deep Learning methods are becoming prominent in automated software bug detection; however, they lack the global understanding of the given code. Consequently, their performance tends to degrade, especially when they are applied to large interconnected code bases or complex modula…

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