Maintenance-Oriented Selection of Software Components. - Pasquale Ardimento; Alessandro Bianchi; Giuseppe Visaggio (CSMR, 2004)

Multiview Framework for Goal Oriented Measurement Plan Design. - Pasquale Ardimento; Maria Teresa Baldassarre; Danilo Caivano; Giuseppe Visaggio (PROFES, 2004)

Empirical Investigation for Building Competences: A case for Extraordinary Maintenance. - Pasquale Ardimento; Alessandro Bianchi; Nicola Boffoli; Giuseppe Visaggio (SEKE, 2005)

Decision Tables for Knowledge Acquisition during Goal Interpretation. - Pasquale Ardimento; Maria Teresa Baldassarre; Danilo Caivano; Giuseppe Visaggio (SEKE, 2005)

Innovation Diffusion through Empirical Studies. - Pasquale Ardimento; Maria Teresa Baldassarre; Danilo Caivano; Giuseppe Visaggio (SEKE, 2005)

Tecnologia per il global software development (GSD). - Pasquale Ardimento (2005)

Assessing multiview framework (MF) comprehensibility and efficiency: A replicated experiment. - Pasquale Ardimento; Maria Teresa Baldassarre; Danilo Caivano; Giuseppe Visaggio (Inf. Softw. Technol., 2006)

A maintenance oriented Framework for software components characterization. - Pasquale Ardimento; Giovanni Bruno; Danilo Caivano; Giuseppe Visaggio (CSMR, 2007)

Empirical Validation on Knowledge Packaging Supporting Knowledge Transfer. - Pasquale Ardimento; Maria Teresa Baldassarre; Marta Cimitile; Giuseppe Visaggio (ICSOFT (PL/DPS/KE/MUSE), 2007)

Empirical Experimentation for Validating the Usability of Knowledge Packages in Transferring Innovations. - Pasquale Ardimento; Maria Teresa Baldassarre; Marta Cimitile; Giuseppe Visaggio (ICSOFT/ENASE (Selected Papers), 2007)

Controlled Experiment on Search Engine Knowledge Extraction Capabilities. - Pasquale Ardimento; Danilo Caivano; Maria Teresa Baldassarre; Marta Cimitile; Giuseppe Visaggio (ICSOFT (PL/DPS/KE), 2008)

An Empirical Study on Software Engineering Knowledge/Experience Packages. - Pasquale Ardimento; Marta Cimitile (PROFES, 2008)

Empirical Investigation of the Efficacy and Efficiency of Tools for Transferring Software Engineering Knowledge. - Pasquale Ardimento; Danilo Caivano; Marta Cimitile; Giuseppe Visaggio (J. Inf. Knowl. Manag., 2008)

Empirical Validation of Knowledge Packages as Facilitators for Knowledge Transfer. - Pasquale Ardimento; Maria Teresa Baldassarre; Marta Cimitile; Giuseppe Visaggio (J. Inf. Knowl. Manag., 2009)

Distributed Software Development with Knowledge Experience Packages. - Pasquale Ardimento; Marta Cimitile; Giuseppe Visaggio (OTM Workshops, 2013)

Building a Knowledge Experience Base for Facilitating Innovation. - Pasquale Ardimento; Vito Nicola Convertini; Giuseppe Visaggio (Int. J. E Serv. Mob. Appl., 2013)

Experience Formalized as a Service for Geographical and Temporal Remote Collaboration. - Pasquale Ardimento; Danilo Caivano; Giuseppe Visaggio (IIAI-AAI, 2014)

Predicting Bug-Fix Time: Using Standard Versus Topic-Based Text Categorization Techniques. - Pasquale Ardimento; Massimo Bilancia; Stefano Monopoli (DS, 2016)

Knowledge extraction from on-line open source bug tracking systems to predict bug-fixing time. - Pasquale Ardimento; Andrea Dinapoli (WIMS, 2017)

A Multi-source Machine Learning Approach to Predict Defect Prone Components. - Pasquale Ardimento; Mario Luca Bernardi; Marta Cimitile (ICSOFT, 2018)

Learning analytics to improve coding abilities: a fuzzy-based process mining approach. - Pasquale Ardimento; Mario Luca Bernardi; Marta Cimitile; Giuseppe De Ruvo (FUZZ-IEEE, 2019)

On the Students' Misconceptions in Object-Oriented Language Constructs. - Pasquale Ardimento; Mario Luca Bernardi; Marta Cimitile (HELMeTO, 2019)

Evaluating coding behavior in software development processes: a process mining approach. - Pasquale Ardimento; Mario Luca Bernardi; Marta Cimitile; Fabrizio Maria Maggi (ICSSP, 2019)

Mining Developer's Behavior from Web-Based IDE Logs. - Pasquale Ardimento; Mario Luca Bernardi; Marta Cimitile; Giuseppe De Ruvo (WETICE, 2019)

Training in a Virtual Learning Environment: A Process Mining Approach. - Annalisa Appice; Pasquale Ardimento; Donato Malerba; Giuseppe Modugno; Diego Marra; Marco Mottola (EAIS, 2020)

Malware Phylogeny Analysis using Data-Aware Declarative Process Mining. - Pasquale Ardimento; Mario Luca Bernardi; Marta Cimitile (EAIS, 2020)

Using BERT to Predict Bug-Fixing Time. - Pasquale Ardimento; Costantino Mele (EAIS, 2020)

Multi Software Product Lines: A Systematic Mapping Study. - Pasquale Ardimento; Nicola Boffoli; Giuseppe Superbo (ENASE, 2020)

Experimentation of Flipped Learning in a University Course on Object-Oriented Programming Paradigm. - Pasquale Ardimento; Michele Scalera (HELMeTO, 2020)

Towards automatic assessment of object-oriented programs. - Pasquale Ardimento; Mario Luca Bernardi; Marta Cimitile (ICSE (Companion Volume), 2020)

Temporal Convolutional Networks for Just-in-Time Software Defect Prediction. - Pasquale Ardimento; Lerina Aversano; Mario Luca Bernardi; Marta Cimitile (ICSOFT, 2020)

Data-Aware Declarative Process Mining for Malware Detection. - Pasquale Ardimento; Lerina Aversano; Mario Luca Bernardi; Marta Cimitile (IJCNN, 2020)

Software Analytics to Support Students in Object-Oriented Programming Tasks: An Empirical Study. - Pasquale Ardimento; Mario Luca Bernardi; Marta Cimitile (IEEE Access, 2020)

Reusing Bugged Source Code to Support Novice Programmers in Debugging Tasks. - Pasquale Ardimento; Mario Luca Bernardi; Marta Cimitile; Giuseppe De Ruvo (ACM Trans. Comput. Educ., 2020)

A Machine Learning Approach for Walker Identification Using Smartphone Sensors. - Antonio Angrisano; Pasquale Ardimento; Mario Luca Bernardi; Marta Cimitile; Salvatore Gaglione (Complex Pattern Mining, 2020)

A Text-Based Regression Approach to Predict Bug-Fix Time. - Pasquale Ardimento; Nicola Boffoli; Costantino Mele (Complex Pattern Mining, 2020)

Using Process Mining to Understand Students' and Teams' Dynamics. - Pasquale Ardimento; Mario Luca Bernardi; Marta Cimitile (HELMeTO, 2021)

Transfer Learning for Just-in-Time Design Smells Prediction using Temporal Convolutional Networks. - Pasquale Ardimento; Lerina Aversano; Mario Luca Bernardi; Marta Cimitile; Martina Iammarino (ICSOFT, 2021)

Deep Neural Networks Ensemble for Lung Nodule Detection on Chest CT Scans. - Pasquale Ardimento; Lerina Aversano; Mario Luca Bernardi; Marta Cimitile (IJCNN, 2021)

Temporal convolutional networks for just-in-time design smells prediction using fine-grained software metrics. - Pasquale Ardimento; Lerina Aversano; Mario Luca Bernardi; Marta Cimitile; Martina Iammarino (Neurocomputing, 2021)

A Supervised Generative Topic Model to Predict Bug-fixing Time on Open Source Software Projects. - Pasquale Ardimento; Nicola Boffoli (ENASE, 2022)

Predicting Bug-Fixing Time Using the Latent Dirichlet Allocation Model with Covariates. - Pasquale Ardimento; Nicola Boffoli (ENASE (Selected Papers), 2022)

Flipping the Laboratory in an Academic Course on Object-Oriented Paradigm. - Pasquale Ardimento; Michele Scalera (HELMeTO, 2022)

Predicting Bug-Fixing Time: DistilBERT Versus Google BERT. - Pasquale Ardimento (PROFES, 2022)

Design patterns mining using neural sub-graph matching. - Pasquale Ardimento; Lerina Aversano; Mario Luca Bernardi; Marta Cimitile (SAC, 2022)

Fuzzy-based Process Mining to Discover the Coding Behavior: Challenges and Future Works. - Pasquale Ardimento; Lerina Aversano; Mario Luca Bernardi; Marta Cimitile (OLUD@WCCI, 2022)

Using deep temporal convolutional networks to just-in-time forecast technical debt principal. - Pasquale Ardimento; Lerina Aversano; Mario Luca Bernardi; Marta Cimitile; Martina Iammarino (J. Syst. Softw., 2022)

Just-in-time software defect prediction using deep temporal convolutional networks. - Pasquale Ardimento; Lerina Aversano; Mario Luca Bernardi; Marta Cimitile; Martina Iammarino (Neural Comput. Appl., 2022)

CENTAURO: An Explainable AI Approach for Customer Loyalty Prediction in Retail Sector. - Giuseppina Andresini; Annalisa Appice; Pasquale Ardimento; Andrea Antonio Brunetta; Antonio Giuseppe Doronzo; Giuseppe Ieva; Francesco Luce; Donato Malerba; Vincenzo Pasquadibisceglie (AI*IA, 2023)

Managing Domain Analysis in Software Product Lines with Decision Tables: An Approach for Decision Representation, Anomaly Detection and Resolution. - Nicola Boffoli; Pasquale Ardimento; Alessandro Nicola Rana (ENASE, 2023)

UML Miner: A Tool for Mining UML Diagrams. - Pasquale Ardimento; Lerina Aversano; Mario Luca Bernardi; Vito Alessandro Carella; Marta Cimitile; Michele Scalera (MoDELS (Companion), 2023)

Enhancing Bug-Fixing Time Prediction with LSTM-Based Approach. - Pasquale Ardimento (PROFES (2), 2023)

Evo-GUNet3++: Using evolutionary algorithms to train UNet-based architectures for efficient 3D lung cancer detection. - Pasquale Ardimento; Lerina Aversano; Mario Luca Bernardi; Marta Cimitile; Martina Iammarino; Chiara Verdone (Appl. Soft Comput., 2023)

Teaching UML using a RAG-based LLM. - Pasquale Ardimento; Mario Luca Bernardi; Marta Cimitile (IJCNN, 2024)

A RAG-based Feedback Tool to Augment UML Class Diagram Learning. - Pasquale Ardimento; Mario Luca Bernardi; Marta Cimitile; Michele Scalera (MoDELS (Companion), 2024)

Enhancing Software Modeling Learning with AI-Powered Scaffolding. - Pasquale Ardimento; Mario Luca Bernardi; Marta Cimitile; Michele Scalera (MoDELS (Companion), 2024)

Back to the Model: UML Miner and the Power of Process Mining. - Pasquale Ardimento; Mario Luca Bernardi; Marta Cimitile; Michele Scalera (ICSOFT, 2025)

A novel LLM-based classifier for predicting bug-fixing time in Bug Tracking Systems. - Pasquale Ardimento; Michele Capuzzimati; Gabriella Casalino; Daniele Schicchi; Davide Taibi 002 (J. Syst. Softw., 2025)