Léuson Da Silva

Léuson Da Silva

Postdoctoral Fellow

Polytechnique Montreal

Biography

I’m a Postdoctoral Fellow at Polytechnique Montreal (Canada) since 2023 working with Prof. Foutse Khomh. I have a P.h.D. Degree in Computer Science at the Federal University of Pernambuco (Brazil) under the supervision of Prof. Paulo Borba, where I still collaborate on the Software Productivity Group. In my research, I investigate how to support developers on their daily tasks, like when dealing with code integration conflicts (build and test conflicts) and code reviews (SE4AI/AI4SE). My research interests are on Large Language Models, Mining Software Repositories, Collaborative Software Development, Empirical Studies, and Software Evolution.

Interests
  • LLMs
  • SE4AI/AI4SE
  • Software Evolution
  • Empirical Studies
Education
  • PhD in Computer Science, 2022

    Federal University of Pernambuco, Brazil - Exchange in Chalmers University (Sweden)

  • MSc in Computer Science, 2018

    Federal University of Pernambuco, Brazil

  • BSc in Software Engineering, 2015

    Federal University of Ceará, Brazil - Exchange in TU Munich (Germany)

Experience

 
 
 
 
 
Polytechnique Montreal
Postdoctoral Fellow
April 2023 – Present Montreal, Canada

Research:

  • Software Engineering for AI
  • AI for SE
  • LLMs
 
 
 
 
 
Catholic University of Pernambuco
Assistant Professor I
March 2022 – March 2023 Recife, Brazil

Undergraduate Courses:

  • Software Engineering
  • Object-Oriented Programming
  • Software Testing
  • Programming Languages Paradigms
 
 
 
 
 
Catholic College of Paraiba
Lecturer
September 2021 – January 2022 Paraíba, Brazil

Undergraduate Courses:

  • Software Testing
 
 
 
 
 
Chalmers University
Research Assistant
October 2019 – January 2020 Gothenburg, Sweden
Research

Publications

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(2025). Logging requirement for continuous auditing of responsible machine learning-based applications. In EMSE.

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(2025). Assessing the adoption of security policies by developers in terraform across different cloud providers. In EMSE.

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(2024). Semantic conflict detection via dynamic analysis. In SBLP.

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(2024). Detecting semantic conflicts with unit tests. Journal of Systems and Software.

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(2022). Build Conflicts in The Wild. Journal of Software: Evolution and Process.

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