ELENCO PUBBLICAZIONI Prof. Pezzè

2005 A Technique for Verifying Component-Based Software Mariani, L., Pezze', M. (2005). A Technique for Verifying Component-Based Software. ELECTRONIC NOTES IN THEORETICAL COMPUTER SCIENCE, 116, 17-30 [10.1016/j.entcs.2004.02.089].1986 Voice and data performance measurements in L-express net Borgonovo, F., Cadorin, E., Fratta, L., Pezze', M. (1986). Voice and data performance measurements in L-express net. In Proceedings of the ACM SIGCOMM conference on Communications architectures & protocols (pp.120-125). ACM [10.1145/18172.18187].2024 Semantic matching in GUI test reuse Khalili, F., Mariani, L., Mohebbi, A., Pezzè, M., Terragni, V. (2024). Semantic matching in GUI test reuse. EMPIRICAL SOFTWARE ENGINEERING, 29(3) [10.1007/s10664-023-10406-8].2023 Prevent: An Unsupervised Approach to Predict Software Failures in Production Denaro, G., Heydarov, R., Mohebbi, A., Pezzè, M. (2023). Prevent: An Unsupervised Approach to Predict Software Failures in Production. IEEE TRANSACTIONS ON SOFTWARE ENGINEERING, 49(12), 5139-5153 [10.1109/TSE.2023.3327583].2022 A Survey of Field-based Testing Techniques Bertolino, A., Braione, P., Angelis, G., Gazzola, L., Kifetew, F., Mariani, L., et al. (2022). A Survey of Field-based Testing Techniques. ACM COMPUTING SURVEYS, 54(5), 1-39 [10.1145/3447240].2022 The Ineffectiveness of Domain-Specific Word Embedding Models for GUI Test Reuse Khalili, F., Mohebbi, A., Terragni, V., Pezze, M., Mariani, L., Heydarnoori, A. (2022). The Ineffectiveness of Domain-Specific Word Embedding Models for GUI Test Reuse. In IEEE International Conference on Program Comprehension (pp.560-564). IEEE Computer Society [10.1145/3524610.3527873].2022 Testing Software in Production Environments with Data from the Field Gazzola, L., Mariani, L., Orru, M., Pezze, M., Tappler, M. (2022). Testing Software in Production Environments with Data from the Field. In Proceedings - 2022 IEEE 15th International Conference on Software Testing, Verification and Validation, ICST 2022 (pp.58-69). Institute of Electrical and Electronics Engineers Inc. [10.1109/ICST53961.2022.00017].2022 Call Me Maybe: Using NLP to Automatically Generate Unit Test Cases Respecting Temporal Constraints Blasi, A., Gorla, A., Ernst, M., Pezze', M. (2022). Call Me Maybe: Using NLP to Automatically Generate Unit Test Cases Respecting Temporal Constraints. In 37th IEEE/ACM International Conference on Automated Software Engineering, ASE 2022. Association for Computing Machinery [10.1145/3551349.3556961].2021 Reusing Solutions Modulo Theories Aquino, A., Denaro, G., Pezze, M. (2021). Reusing Solutions Modulo Theories. IEEE TRANSACTIONS ON SOFTWARE ENGINEERING, 47(5), 948-968 [10.1109/TSE.2019.2898199].

 

 

ELENCO PUBBLICAZIONI CONDIVISE

2024 EEG Acquisition and Motor Imagery Classification for Robotic Control Amrani, H., Micucci, D., Nalin, M., Napoletano, P., Rizzi, I. (2024). EEG Acquisition and Motor Imagery Classification for Robotic Control. In 2024 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) (pp.1-4). Institute of Electrical and Electronics Engineers Inc. [10.1109/EMBC53108.2024.10782723].2020 Measuring software testability modulo test quality Terragni, V., Salza, P., Pezze', M. (2020). Measuring software testability modulo test quality. In ICPC '20: Proceedings of the 28th International Conference on Program Comprehension (pp.241-251). IEEE Computer Society [10.1145/3387904.3389273].2020 Evolutionary improvement of assertion oracles Terragni, V., Jahangirova, G., Tonella, P., Pezze', M. (2020). Evolutionary improvement of assertion oracles. In ESEC/FSE 2020 - Proceedings of the 28th ACM Joint Meeting European Software Engineering Conference and Symposium on the Foundations of Software Engineering (pp.1178-1189). Association for Computing Machinery, Inc [10.1145/3368089.3409758].2022 Call Me Maybe: Using NLP to Automatically Generate Unit Test Cases Respecting Temporal Constraints Blasi, A., Gorla, A., Ernst, M., Pezze', M. (2022). Call Me Maybe: Using NLP to Automatically Generate Unit Test Cases Respecting Temporal Constraints. In 37th IEEE/ACM International Conference on Automated Software Engineering, ASE 2022. Association for Computing Machinery [10.1145/3551349.3556961].2021 MeMo: Automatically identifying metamorphic relations in Javadoc comments for test automation Blasi, A., Gorla, A., Ernst, M., Pezze', M., Carzaniga, A. (2021). MeMo: Automatically identifying metamorphic relations in Javadoc comments for test automation. THE JOURNAL OF SYSTEMS AND SOFTWARE, 181 [10.1016/j.jss.2021.111041].2024 Scoping Software Engineering for AI: The TSE Perspective Uchitel, S., Chechik, M., Penta, M., Adams, B., Aguirre, N., Bavota, G., et al. (2024). Scoping Software Engineering for AI: The TSE Perspective. IEEE TRANSACTIONS ON SOFTWARE ENGINEERING, 50(11), 2709-2711 [10.1109/TSE.2024.3470368].2024 Waste Management Through Digital Twins and Business Process Modeling Di Salle, A., Fedeli, A., Iovino, L., Mariani, L., Micucci, D., Rebelo, L., et al. (2024). Waste Management Through Digital Twins and Business Process Modeling. In MODELS Companion '24: Proceedings of the ACM/IEEE 27th International Conference on Model Driven Engineering Languages and Systems (pp.513-517). Association for Computing Machinery, Inc [10.1145/3652620.3687796].2024 A Data-Driven Approach Supporting Location Decisions for Docking Stations in Bike-Sharing Systems Spahiu, B., Briola, D., Sartori, R., Vizzari, G. (2024). A Data-Driven Approach Supporting Location Decisions for Docking Stations in Bike-Sharing Systems. In 27th European Conference on Artificial Intelligence, 19–24 October 2024, Santiago de Compostela, Spain – Including 13th Conference on Prestigious Applications of Intelligent Systems (PAIS 2024) (pp.4618-4625) [10.3233/faia241056].2024 Curriculum-Based RL for Pedestrian Simulation: Sensitivity Analysis and Hyperparameter Exploration Vizzari, G., Briola, D., Pisapia, F. (2024). Curriculum-Based RL for Pedestrian Simulation: Sensitivity Analysis and Hyperparameter Exploration. In Thirteenth International Workshop on Agents in Traffic and Transportation co-located with the the 27th European Conference on Artificial Intelligence (ECAI 2024) (pp.136-149). CEUR-WS.2024 DBInputs: Exploiting Persistent Data to Improve Automated GUI Testing Clerissi, D., Denaro, G., Mobilio, M., Mariani, L. (2024). DBInputs: Exploiting Persistent Data to Improve Automated GUI Testing. IEEE TRANSACTIONS ON SOFTWARE ENGINEERING, 50(9), 2412-2436 [10.1109/TSE.2024.3439002].2024 Towards Model-Driven Dashboard Generation for Systems-of-Systems Rossi, M., Tundo, A., Mariani, L. (2024). Towards Model-Driven Dashboard Generation for Systems-of-Systems. In SESoS '24: Proceedings of the 12th ACM/IEEE International Workshop on Software Engineering for Systems-of-Systems and Software Ecosystems (pp.9-12). Association for Computing Machinery, Inc [10.1145/3643655.3643876].2024 Continuous Conformance of Software Architectures Bucaioni, A., Di Salle, A., Iovino, L., Mariani, L., Pelliccione, P. (2024). Continuous Conformance of Software Architectures. In Proceedings - IEEE 21st International Conference on Software Architecture, ICSA 2024 (pp.112-122). Institute of Electrical and Electronics Engineers Inc. [10.1109/ICSA59870.2024.00019].2024 Testing in the Evolving World of DL Systems: Insights from Python GitHub Projects Ali, Q., Riganelli, O., Mariani, L. (2024). Testing in the Evolving World of DL Systems: Insights from Python GitHub Projects. In IEEE International Conference on Software Quality, Reliability and Security, QRS (pp.25-35). Institute of Electrical and Electronics Engineers Inc. [10.1109/QRS62785.2024.00013].2024 ReProbe: An Architecture for Reconfigurable and Adaptive Probes Alessi, F., Tundo, A., Mobilio, M., Riganelli, O., Mariani, L. (2024). ReProbe: An Architecture for Reconfigurable and Adaptive Probes. In Proceedings - IEEE 21st International Conference on Software Architecture Companion, ICSA-C 2024 (pp.175-178). Institute of Electrical and Electronics Engineers Inc. [10.1109/ICSA-C63560.2024.00037].2024 Creating Virtual Reality Scenarios for Pedestrian Experiments Focusing on Social Interactions Briola, D., Tinti, F., Vizzari, G. (2024). Creating Virtual Reality Scenarios for Pedestrian Experiments Focusing on Social Interactions. In Proceedings of the 25th Workshop "From Objects to Agents" (pp.170-185). CEUR-WS.2024 The future of human and animal digital health platforms Bok, P., Micucci, D. (2024). The future of human and animal digital health platforms. JOURNAL OF RELIABLE INTELLIGENT ENVIRONMENTS, 10(3), 245-256 [10.1007/s40860-024-00232-0].2024 FILO: Automated FIx-LOcus Identification for Android Framework Compatibility Issues Mobilio, M., Riganelli, O., Micucci, D., Mariani, L. (2024). FILO: Automated FIx-LOcus Identification for Android Framework Compatibility Issues. INFORMATION, 15(8) [10.3390/info15080423].2024 Can Digital Tools Save Lives? A Systematic Review of Apps and Web-Based Interventions for Suicide Prevention in Post-Discharge Poli, M., Fooroogh Mand Arabi, A., Russotto, S., Turolla, F., Nembrini, F., Micucci, D., et al. (2024). Can Digital Tools Save Lives? A Systematic Review of Apps and Web-Based Interventions for Suicide Prevention in Post-Discharge. Intervento presentato a: Convegno Internazionale di Suicidologia e Salute Pubblica, Roma, Italia.2024 Analyzing Prompt Influence on Automated Method Generation: An Empirical Study with Copilot Fagadau, I., Mariani, L., Micucci, D., Riganelli, O. (2024). Analyzing Prompt Influence on Automated Method Generation: An Empirical Study with Copilot. In ICPC '24: Proceedings of the 32nd IEEE/ACM International Conference on Program Comprehension (pp.24-34). IEEE Computer Society [10.1145/3643916.3644409].2024 Generating Java Methods: An Empirical Assessment of Four AI-Based Code Assistants Corso, V., Mariani, L., Micucci, D., Riganelli, O. (2024). Generating Java Methods: An Empirical Assessment of Four AI-Based Code Assistants. In Proceedings of the 32nd IEEE/ACM International Conference on Program Comprehension (pp.13-23). IEEE [10.1145/3643916.3644402].2024 Assessing AI-Based Code Assistants in Method Generation Tasks Corso, V., Mariani, L., Micucci, D., Riganelli, O. (2024). Assessing AI-Based Code Assistants in Method Generation Tasks. In Proceedings - International Conference on Software Engineering (pp.380-381). IEEE Computer Society [10.1145/3639478.3643122].2024 Deep Representation Learning for Open Vocabulary Electroencephalography-to-Text Decoding Amrani, H., Micucci, D., Napoletano, P. (2024). Deep Representation Learning for Open Vocabulary Electroencephalography-to-Text Decoding. IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS, 1-12 [10.1109/JBHI.2024.3416066].2024 A Role and Reward Analysis in Off-chain Mechanisms for Executing MEV Strategies in Ethereum Proof-of-Stake Mancino, D., Leporati, A., Viviani, M., Denaro, G. (2024). A Role and Reward Analysis in Off-chain Mechanisms for Executing MEV Strategies in Ethereum Proof-of-Stake. DISTRIBUTED LEDGER TECHNOLOGIES [10.1145/3672405].2024 Anonymizing Test Data in Android: Does It Hurt? Masserini, E., Ginelli, D., Micucci, D., Briola, D., Mariani, L. (2024). Anonymizing Test Data in Android: Does It Hurt?. In Proceedings of the 5th ACM/IEEE International Conference on Automation of Software Test (AST 2024) (pp.88-98). Association for Computing Machinery, Inc [10.1145/3644032.3644463].2024 MutaBot: A Mutation Testing Approach for Chatbots Urrico, M., Clerissi, D., Mariani, L. (2024). MutaBot: A Mutation Testing Approach for Chatbots. In ICSE-Companion '24: Proceedings of the 2024 IEEE/ACM 46th International Conference on Software Engineering: Companion Proceedings (pp.79-83). IEEE Computer Society [10.1145/3639478.3640032].2024 Semantic matching in GUI test reuse Khalili, F., Mariani, L., Mohebbi, A., Pezzè, M., Terragni, V. (2024). Semantic matching in GUI test reuse. EMPIRICAL SOFTWARE ENGINEERING, 29(3) [10.1007/s10664-023-10406-8].2024 Measuring Software Testability via Automatically Generated Test Cases Guglielmo, L., Mariani, L., Denaro, G. (2024). Measuring Software Testability via Automatically Generated Test Cases. IEEE ACCESS, 12, 63904-63916 [10.1109/access.2024.3396625].2023 Curriculum–Based Reinforcement Learning for Pedestrian Simulation: Towards an Explainable Training Process Vizzari, G., Briola, D., Cecconello, T. (2023). Curriculum–Based Reinforcement Learning for Pedestrian Simulation: Towards an Explainable Training Process. In Proceedings of the 24th Workshop "From Objects to Agents" (pp.32-48). CEUR-WS.2024 A family of experiments about how developers perceive delayed system response time Cornejo, O., Briola, D., Micucci, D., Ginelli, D., Mariani, L., Santos Parrilla, A., et al. (2024). A family of experiments about how developers perceive delayed system response time. SOFTWARE QUALITY JOURNAL, 32(2), 567-605 [10.1007/s11219-024-09660-w].

 

 

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