Markos Viggiato

About Me

I am a Ph.D. researcher at the Analytics of Software, GAmes And Repository Data (ASGAARD) lab, at the University of Alberta. I received my M.Sc. degree in Computer Science and the B.E. degree in Control and Automation Engineering from the Federal University of Minas Gerais (UFMG), Brazil.
I am extremely enthusiastic about how data analytics and AI can play an important role in different fields, such as games: from game design to gameplay to game data analysis. I am eager to advance and apply data analytics, machine learning, and AI techniques to support and help people from different industry segments.


My research interests include data science, machine learning, and artificial intelligence applied to different industry segments, such as the gaming and the software development segments. Overall, I am interested in leveraging those techniques with publicly available data to better understand the state-of-the-practice and obtain actionable insights.

In my Ph.D., I have conducted research in applied machine learning and data analytics using computer game data, such as game logs and user-provided game reviews. The main goal of my Ph.D. is to enable more effective approaches to leverage publicly available game data to improve data analytics techniques.

During my M.Sc., I mined hundreds of GitHub projects and leveraged machine learning and statisical techniques to understand how developers perform code changes in mobile and non-mobile platforms. I also conducted interviews and surveys to investigate how software development practices vary across different industry segments, such as healthcare, games and financial segments.


Please check my projects below.

xAI for Dota 2

Explainable prediction models

Game Review Sentiment

Sentiment classification of game reviews

Real-time Analytics

Real-time analytics for news

Code Change Evolution

Co-evolution of changes on GitHub


Google Scholar profile


What Causes Wrong Sentiment Classifications of Game Reviews?
Markos Viggiato, Dayi Lin, Abram Hindle, and Cor-Paul Bezemer
IEEE Transactions on Games (2021)


Understanding machine learning software defect predictions
Geanderson Esteves, Eduardo Figueiredo, Adriano Veloso, Markos Viggiato, Nivio Ziviani
Automated Software Engineering Journal (2020)

Trouncing in Dota 2: An Investigation of Blowout Matches
Markos Viggiato, Cor-Paul Bezemer
The 16th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment (AIIDE 2020), Worcester, USA (to be held virtually due to covid 19)

Predicting Software Defects with Explainable Machine Learning
Geanderson Esteves, Eduardo Figueiredo, Adriano Veloso, Markos Viggiato, Nivio Ziviani
The 19th Brazilian Symposium on Software Quality (SBQS 2020), (held virtually)

Testing Configurable Software Systems: The Failure Observation Challenge
Fischer Ferreira, Markos Viggiato, Mauricio Souza, Eduardo Figueiredo
The 24th International Systems and Software Product Line Conference (SPLC 2020), Montreal, Canada (to be held virtually due to covid 19)


Feature Changes in Source Code for Commit Classification Into Maintenance Activities
Richard V. R. Mariano, Geanderson E. dos Santos, Markos Viggiato, Wladmir C. Brandao
The 18th International Conference on Machine Learning and Applications (ICMLA 2019), Boca Raton, USA

How Do Code Changes Evolve in Different Platforms? A Mining-based Investigation
Markos Viggiato, Johnatan Oliveira, Eduardo Figueiredo, Pooyan Jamshidi, Christian Kastner
The 35th International Conference on Software Maintenance and Evolution (ICSME 2019), Cleveland, USA

How Well Do You Know This Library? Mining Experts from Source Code Analysis
Johnatan Oliveira, Markos Viggiato, Eduardo Figueiredo
The 18th Brazilian symposium on Software Quality (SBQS 2019), Fortaleza, Brazil

Understanding Similarities and Differences in Software Development Practices Across Domains
Markos Viggiato, Johnatan Oliveira, Eduardo Figueiredo, Pooyan Jamshidi, Christian Kastner
The 14th International Conference on Global Software Engineering (ICGSE 2019), Montreal, Canada


Evaluating Domain-Specific Metric Thresholds: An Empirical Study
Allan Mori, Gustavo Vale, Markos Viggiato, Johnatan Oliveira, Eduardo Figueiredo, Elder Cirilo, Pooyan Jamshidi, Christian Kastner
The 1st International Conference on Technical Debt (TechDebt 2018), Gothenburg, Sweden

An Empirical Study on the Impact of Android Code Smells on Resource Usage
Johnatan Oliveira, Markos Viggiato, Mateus Santos, Eduardo Figueiredo, Humberto Marques-Neto
The 30th International Conference on Software Engineering and Knowledge Engineering (SEKE 2018), Redwood City, San Francisco Bay, USA

Microservices in Practice: A Survey Study
Markos Viggiato, Ricardo Terra, Henrique Rocha, Marco Tulio Valente, Eduardo Figueiredo
The 6th Workshop on Software Visualization, Evolution and Maintenance (VEM 2018), Sao Carlos, Brazil


On the Investigation of Domain-Sensitive Bad Smells in Information Systems (Extended version)
Markos Viggiato, Johnatan Oliveira, Cleiton Tavares, Eduardo Figueiredo
INFOCOMP Journal of Computer Science (2017)

On the Investigation of Domain-Sensitive Bad Smells in Information Systems
Markos Viggiato, Johnatan Oliveira, Eduardo Figueiredo
The 13th Brazilian Symposium on Information Systems (SBSI 2017), Lavras, Brazil


Please find below my resume and CV.

Resume CV

Contact Me

If you have any questions or would like to talk about my research or projects, please feel free to send me an email at:

  • markosviggiato [at] or viggiato [at]

Feel free to reach me out through my professional networks as well.