“One accurate measurement is worth a thousand expert opinions.”
— Grace Hopper
Basic Information
- Born
- 1995
- Birthplace
- Milano
- Living in
- Legnano
- biaggi.jack@gmail.com
About me
I’m a young computer scientist interested in software engineering and cutting-edge technologies. I’m also interested in sci-fi movies and TV series, from which I take inspiration for the future. I strongly believe that technology makes the world a better place to live, so I make the main core of my life out of it.
Education
Master of Science in Computer Science at University of Milano - Bicocca
Thesis: Automated and Personalized Code Anomlies Detection
Areas of interest:
- Software Engineering
- Software Architecture
- Reverse Engineering
- Technical Debt
- Software Quality
Bachelor of Science in Computer Science at University of Milano - Bicocca
Thesis: An Architectural Smells Detection Tool for C and C++ Projects.
Experience
Software Engineer at UniCredit Services
Design of cybersecurity solutions for UniCredit mobile banking.
Software Engineer at NTT Data
Development of cybersecurity solutions for UniCredit Services.
Full Stack Developer at Myco
Re-engineering and migration of a web application for continuous feedback.
Researcher at University of Milano - Bicocca
Detection of performance antipatterns in Java applications through the analysis of profiling data extracted during the execution of load tests.
Mobile Developer at Outpump
Android Developer for a news website.
Research Assistant
Academic collaboration in a research project for an industrial case study in a big automotive company located in Gothenburg, Sweden.
Student Tutor at University of Milano - Bicocca
Academic tutoring for the course of Software Analysis and Design.
Publications
Martini, A., Fontana, F. A., Biaggi, A., & Roveda, R. (2018, September).
Identifying and prioritizing architectural debt through architectural smells: a case study in a large software company.
In European Conference on Software Architecture (pp. 320-335). Springer, Cham.
Biaggi, A., Fontana, F. A., & Roveda, R. (2018, August).
An Architectural Smells Detection Tool for C and C++ Projects.
In 2018 44th Euromicro Conference on Software Engineering and Advanced Applications (SEAA) (pp. 417-420). IEEE.
Skills
Programming Languages
- Java
- Python
- C/C++
- R
- JavaScript
Technologies
- Android
- Spring Boot
- Docker
- PostgreSQL Database
- MySQL Database
- Oracle Database
- JUnit
- Selenium
- SonarQube
- Git
Languages
| Language | Level |
|---|---|
| Italian | Mother tongue |
| English | C1 |