Antonio Guerriero
IoT Research Lab · Università degli Studi di Salerno
Ph.D. in Information Technologies and Electrical Engineering (ITEE) and tenure-track researcher (RTT) at Università degli Studi di Salerno. His research interests include software testing, software reliability, testing of autonomous systems, and Internet of Things (IoT) with a focus on TinyML and federated learning for resource-constrained devices.
Research Interests
- Artificial Intelligence
- Software Reliability
- Software Testing
- Internet of Things (IoT)
- TinyML
- Federated Learning
Education
PhD in Information Technology and Electrical Engineering
University of Naples Federico II
2022
M.Sc. in Computer Engineering
University of Naples Federico II
2018
B.Sc. in Computer Engineering
University of Naples Federico II
2014
Publications
2026
Analyzing the Effect of Attention Functions in Autoencoder-Based Network Anomaly Detection
Model-Heterogeneous Federated Learning for TinyML in IoT
2025
Causal reasoning in Software Quality Assurance: A systematic review
On-device training and pruning for energy saving and continuous learning in resource-constrained MCUs
Detecting DDoS Attacks in Microservice Architectures via AI-Based Agents
Adaptive Probabilistic Operational Testing for Large Language Models Evaluation
Microservices Performance Testing with Causality-enhanced Large Language Models
A benchmark for ddos attacks detection in microservice architectures
Learning-based Automated Generation of Critical Workload Configurations for Microservices Performance Testing
Multivariate anomaly detection and root cause analysis of energy issues in microservice-based systems
2024
Federated learning for IoT devices: Enhancing TinyML with on-board training
Monitoring tools for DevOps and microservices: A systematic grey literature review
Causality-driven testing of autonomous driving systems
Automated functional and robustness testing of microservice architectures
Identifying performance issues in microservice architectures through causal reasoning
DeepSample: DNN sampling-based testing for operational accuracy assessment
Anomaly detection and root cause analysis of microservices energy consumption
2023
DevOpRET: Continuous reliability testing in DevOps
An empirical evaluation of the energy and performance overhead of monitoring tools on docker-based systems
Iterative Assessment and Improvement of DNN Operational Accuracy
Assessing operational accuracy of cnn-based image classifiers using an oracle surrogate
2022
Microservices integrated performance and reliability testing
Automated grey-box testing of microservice architectures
Assessing black-box test case generation techniques for microservices
2021
Operation is the hardest teacher: estimating DNN accuracy looking for mispredictions
2020
Learning-to-rank vs ranking-to-learn: Strategies for regression testing in continuous integration
Testing microservice architectures for operational reliability
Reliability Evaluation of ML systems, the oracle problem
2019
A hybrid framework for web services reliability and performance assessment
2018
Run-time reliability estimation of microservice architectures
Unknown
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