Giovani Guizzo

Registered user since Fri 10 Jul 2020

Name:Giovani Guizzo
Bio:

Since June 2019 I hold the position of Research Fellow at CREST - Department of Computer Science - University College London (UCL) - London, UK. My research supervisors are Dr. Federica Sarro and Professor Mark Harman.

I obtained my PhD degree in Computer Science at the Department of Informatics - Federal University of ParanĂ¡ (UFPR) - Curitiba, Brazil, under the supervision of Professor Silvia Regina Vergilio in 2018.

My main research interest is Search Based Software Engineering (SBSE), mainly focused on Software Testing and Evolutionary Computation. My recent work include Hyper-Heuristics, Evolutionary Algorithms, Multi-Objective Optimization, Automatic Algorithm Generation, Software Design, Design Patterns, Mutation Testing, and others.

Country:United Kingdom
Affiliation:University College London
Research interests:Software Engineering, Optimisation Algorithms

Contributions

SSBSE 2021 Session Chair of SSBSE Session 4 (part of Research Papers)
Committee Member in NIER within the NIER - New Ideas and Emerging Results -track
Author of Refining Fitness Functions for Search-Based Automated Program Repair: A Case Study with ARJA and ARJA-e within the Challenge-track
ASE 2021 Committee Member in Program Committee within the Artifact Evaluation-track
Mutation 2021 Committee Member in Program Committee within the Mutation 2021-track
ESEC/FSE 2021 Committee Member in Program Committee within the Demonstrations-track
ESEC/FSE 2020 Panelist of Conversations on Testing 3 within the Paper Presentations-track
Author of Cost Measures Matter for Mutation Testing Study Validity within the Research Papers-track
ICSE 2021 Author of Enhancing Genetic Improvement of Software with Regression Test Selection within the Technical Track-track
Committee Member in Program Committee within the Posters-track
Author of Artifact for Enhancing Genetic Improvement of Software with Regression Test Selection within the AE - Artifact Evaluation-track
Author of Sentinel: A Hyper-Heuristic for the Generation of Mutant Reduction Strategies within the Journal-First Papers-track