Software Engineering | Software Testing | SE4AI & AI4SE | Postdoctoral Researcher at USI.
I am interested in software testing 🧪 with a particular focus on test generation. I have built tools to automatically generate tests for Web applications 🌐 and Deep Reinforcement Learning 🤖 agents. I am also proficient in testing Self-driving car software in simulation, and in training DL/RL models to drive a small-scale physical vehicle 🚗.
In the following I list my most relevant projects in reversed chronological order:
- qgrams: Web test suite generator integrating different diversity-based techniques
- muPRL: a mutation testing tool for RL agents
- GenBo: a test generator that generates boundary conditions to test and improve a self-driving model
- CPS Tool Competition Pipeline: a test generation pipeline to test self-driving models using the BeamNG simulator
- Maxibon: digital siblings framework for assessing the sim-to-real gap when testing a self-driving model
- Indago: a test generator for RL agents
- AlphaTest: a test generator to assess the plasticity of RL agents
- ART-Qgrams: a test generator for Web applications that uses diversity to evaluate the quality of candidate test cases
- Dante: a test generator that generates boundary conditions to test and improve a self-driving model
- TEDD: dependency detection tool for E2E Web test suites
- DIG: first version of a Web test suite generator using diversity; the generator also integrates Evosuite to generate Web tests using search-based techniques.