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.
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Publications
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Journal articles
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Conference papers
Research Interests
- Artificial Intelligence
- Software Reliability
- Software Testing
- Internet of Things (IoT)
- TinyML
- Federated Learning
Education
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2022
PhD in Information Technology and Electrical Engineering
University of Naples Federico II
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2018
M.Sc. in Computer Engineering
University of Naples Federico II
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2014
B.Sc. in Computer Engineering
University of Naples Federico II
Publications
Google Scholar profile →2026
Analyzing the Effect of Attention Functions in Autoencoder-Based Network Anomaly Detection
Schema-Constrained Document-Level Event Argument Extraction with Lightweight LLM Fine-Tuning
Using Federated Learning for Multimodal Semantic Segmentation in Drones
2025
Causal reasoning in Software Quality Assurance: A systematic review
Learning-based Automated Generation of Critical Workload Configurations for Microservices Performance Testing
Microservices performance testing with causality-enhanced large language models
Adaptive Probabilistic Operational Testing for Large Language Models Evaluation
Detecting DDoS attacks in microservice architectures via AI-based agents
Multivariate anomaly detection and root cause analysis of energy issues in microservice-based systems
A benchmark for DDoS attacks detection in microservice architectures
On-device training and pruning for energy saving and continuous learning in resource-constrained MCUs
Energy-Aware TinyML for Intrusion Detection in IoT Networks
Comparing Model Compression Techniques for MCU-Based Federated TinyML
2024
Automated functional and robustness testing of microservice architectures
Monitoring tools for DevOps and microservices: A systematic grey literature review
Federated learning for IoT devices: Enhancing TinyML with on-board training
Causality-driven testing of autonomous driving systems
DeepSample: DNN sampling-based testing for operational accuracy assessment
Identifying performance issues in microservice architectures through causal reasoning
Anomaly detection and root cause analysis of microservices energy consumption
2023
DevOpRET: Continuous reliability testing in DevOps
Assessing operational accuracy of cnn-based image classifiers using an oracle surrogate
Iterative Assessment and Improvement of DNN Operational Accuracy
An empirical evaluation of the energy and performance overhead of monitoring tools on docker-based systems
2022
Microservices integrated performance and reliability testing
Assessing black-box test case generation techniques for microservices
Automated grey-box testing of microservice architectures
2021
Operation is the hardest teacher: estimating DNN accuracy looking for mispredictions
2020
Testing microservice architectures for operational reliability
Learning-to-rank vs ranking-to-learn: Strategies for regression testing in continuous integration
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
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Contact
Address
Università degli Studi di Salerno
Via Giovanni Paolo II, 132
84084 Fisciano (SA), Italy