Publications

Journal Papers

Antonio Trovato, Manuel De Stefano, Fabiano Pecorelli, Dario Di Nucci, Andrea De Lucia
Reformulating Regression Test Suite Optimization using Quantum Annealing - an Empirical Study
International Journal on Software Tools for Technology Transfer, 2024
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Conference Papers

Denivan Campos, Luana Martins, Emanuela Guglielmi, Michele Tucci, Daniele Di Pompeo,
Simone Scalabrino, Vittorio Cortellessa, Dario Di Nucci, Rocco Oliveto
Identifying and Replicating Code Patterns Driving Performance Regressions in Software Systems
22nd International Conference on Mining Software Repositories (MSR) - Registered Reports, 2025
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Federico Di Menna, Luca Traini, Gabriele Bavota, Vittorio Cortellessa
Investigating Execution-Aware Language Models for Code Optimization
33rd International Conference on Program Comprehension (ICPC, RENE track), 2025
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Antonio Trovato, Luca Traini, Federico Di Menna, Dario Di Nucci
AMBER: AI-Enabled Java Microbenchmark Harness
18th IEEE International Conference on Software Testing, Verification and Validation (ICST), 2025
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Luca Traini, Federico Di Menna, and Vittorio Cortellessa.
AI-driven Java Performance Testing: Balancing Result Quality with Testing Time.
39th IEEE/ACM International Conference on Automated Software Engineering (ASE), 2024
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Muhammad Imran, Vittorio Cortellessa, Davide Di Ruscio, Riccardo Rubei, Luca Traini
An Empirical Study on Code Coverage of Performance Testing
28th International Conference on Evaluation and Assessment in Software Engineering (EASE), 2024
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Vittorio Cortellessa, Daniele Di Pompeo, Michele Tucci
Exploring sustainable alternatives for the deployment of microservices architectures in the cloud
21st IEEE International Conference on Software Architecture (ICSA), 2024
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Federico Di Menna, Luca Traini, Vittorio Cortellessa
Time Series Forecasting of Runtime Software Metrics: An Empirical Study
15th ACM/SPEC International Conference on Performance Engineering (ICPE), 2024
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Workshop Papers

Antonio Trovato, Martin Beseda, Dario Di Nucci
A Preliminary Investigation on the Usage of Quantum Approximate Optimization Algorithms for Test Case Selection
Empirical Studies for Quantum Software Engineering workshop (E-QSE) co-located with EASE, 2025
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