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DanielAndersonTI/README.md

Daniel Anderson de Souza Silva

Master's student in Computer Science — UFCG · Agentic Software Engineering

I study how LLM agents decompose monoliths into microservices — and how to verify that the architecture they produce is internally coherent when there is no reference answer to compare against.

What I'm building

Project What it does
DAVINCI Five-agent pipeline that turns a monolith's user stories into a microservice decomposition. Empirical protocol: 8 systems × 5 agent configurations × 3 LLMs × 3 rounds at temperature 0.0.
Evaluation Framework Structural adherence metrics between a generated architecture and the source monolith.
Experiment-Agents-Tests Reproducibility protocol for agent-based code generation experiments.

📧 daniel.silva@embedded.ufcg.edu.br · LinkedIn

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  1. analise-dados-capes-pos-graduacao-2021-2024 analise-dados-capes-pos-graduacao-2021-2024 Public

    Análise exploratória de dados da CAPES sobre cursos e discentes de pós-graduação no Brasil entre 2021 e 2024, com uso de Python, pandas, estatística descritiva e visualização de dados.

    Jupyter Notebook 1

  2. DAVINCI DAVINCI Public

    An experimental pipeline for evaluating multi-agent approaches to software architecture decomposition using Large Language Models (LLMs), with a focus on identifying services and inter-service inte…

    Python 1

  3. Experiment-Agents-Tests Experiment-Agents-Tests Public

    This project is about testing AI agents to improve their effectiveness in generating architectural suggestions for decomposing monolithic applications into microservices.

    Python 1

  4. LLM-Based-Microservice-Decomposition-Evaluation-Framework LLM-Based-Microservice-Decomposition-Evaluation-Framework Public

    Framework for evaluating the structural adherence of LLM-generated microservice architectures against real monolithic source code.

    Python 1

  5. multiagent-microservice-architecture-generation multiagent-microservice-architecture-generation Public

    Multi‑agent framework (CrewAI + LangChain) that generates microservice decompositions from textual requirements using LLMs

    Python 1

  6. WordEmbeddings WordEmbeddings Public

    Intrinsic evaluation and qualitative probing of GloVe word embeddings with Gensim: analogies, similarity benchmarks, polysemy, dimensionality reduction, and gender bias analysis.

    Jupyter Notebook