Classifying code comments in Java open-source software systems. - Luca Pascarella; Alberto Bacchelli (MSR, 2017)

Classifying code comments in Java mobile applications. - Luca Pascarella (MOBILESoft@ICSE, 2018)

Self-reported activities of Android developers. - Luca Pascarella; Franz-Xaver Geiger; Fabio Palomba; Dario Di Nucci; Ivano Malavolta; Alberto Bacchelli (MOBILESoft@ICSE, 2018)

A graph-based dataset of commit history of real-world Android apps. - Franz-Xaver Geiger; Ivano Malavolta; Luca Pascarella; Fabio Palomba; Dario Di Nucci; Alberto Bacchelli (MSR, 2018)

How is video game development different from software development in open source? - Luca Pascarella; Fabio Palomba; Massimiliano Di Penta; Alberto Bacchelli (MSR, 2018)

Re-evaluating method-level bug prediction. - Luca Pascarella; Fabio Palomba; Alberto Bacchelli (SANER, 2018)

Investigating type declaration mismatches in Python. - Luca Pascarella; Achyudh Ram; Azqa Nadeem; Dinesh Bisesser; Norman Knyazev; Alberto Bacchelli (MaLTeSQuE, 2018)

Information Needs in Contemporary Code Review. - Luca Pascarella; Davide Spadini; Fabio Palomba; Magiel Bruntink; Alberto Bacchelli (Proc. ACM Hum. Comput. Interact., 2018)

Information Needs in Contemporary Code Review - Appendix. - Luca Pascarella; Davide Spadini; Fabio Palomba; Magiel Bruntink; Alberto Bacchelli (Zenodo, 2018)

Information Needs in Contemporary Code Review - Appendix. - Luca Pascarella; Davide Spadini; Fabio Palomba; Magiel Bruntink; Alberto Bacchelli (Zenodo, 2018)

On the Performance of Method-Level Bug Prediction: A Negative Result. Appendix. - Luca Pascarella; Fabio Palomba; Alberto Bacchelli (Zenodo, 2018)

Fine-Grained Just-In-Time Defect Prediction - Appendix. - Luca Pascarella; Fabio Palomba; Alberto Bacchelli (Zenodo, 2018)

Healthcare Android apps: a tale of the customers' perspective. - Mariaclaudia Nicolai; Luca Pascarella; Fabio Palomba; Alberto Bacchelli (WAMA@ESEC/SIGSOFT FSE, 2019)

On The Effect Of Code Review On Code Smells. - Luca Pascarella; Davide Spadini; Fabio Palomba; Alberto Bacchelli (CoRR, 2019)

Classifying code comments in Java software systems. - Luca Pascarella; Magiel Bruntink; Alberto Bacchelli (Empir. Softw. Eng., 2019)

Fine-grained just-in-time defect prediction. - Luca Pascarella; Fabio Palomba; Alberto Bacchelli (J. Syst. Softw., 2019)

On the performance of method-level bug prediction: A negative result. - Luca Pascarella; Fabio Palomba; Alberto Bacchelli (J. Syst. Softw., 2020)

Augmented Fine-Grained Defect Prediction for Code Review. - Luca Pascarella (2020)

Dataset of the paper "Information Needs in Contemporary Code Review". - Luca Pascarella; Davide Spadini; Fabio Palomba; Alberto Bacchelli (Zenodo, 2020)

Evaluating SZZ Implementations Through a Developer-informed Oracle. - Giovanni Rosa; Luca Pascarella; Simone Scalabrino; Rosalia Tufano; Gabriele Bavota; Michele Lanza 001; Rocco Oliveto (ICSE, 2021)

Towards Automating Code Review Activities. - Rosalia Tufano; Luca Pascarella; Michele Tufano; Denys Poshyvanyk; Gabriele Bavota (ICSE, 2021)

An Empirical Study on Code Comment Completion. - Antonio Mastropaolo; Emad Aghajani; Luca Pascarella; Gabriele Bavota (ICSME, 2021)

Logging Practices with Mobile Analytics: An Empirical Study on Firebase. - Julian Harty; Haonan Zhang; Lili Wei 001; Luca Pascarella; Maurício Aniche; Weiyi Shang (MOBILESoft@ICSE, 2021)

An Empirical Study on the Usage of BERT Models for Code Completion. - Matteo Ciniselli; Nathan Cooper; Luca Pascarella; Denys Poshyvanyk; Massimiliano Di Penta; Gabriele Bavota (MSR, 2021)

Regularity or Anomaly? On The Use of Anomaly Detection for Fine-Grained JIT Defect Prediction. - Francesco Lomio; Luca Pascarella; Fabio Palomba; Valentina Lenarduzzi (SEAA, 2022)

Using Deep Learning to Generate Complete Log Statements. - Antonio Mastropaolo; Luca Pascarella; Gabriele Bavota (ICSE, 2022)

Using Pre-Trained Models to Boost Code Review Automation. - Rosalia Tufano; Simone Masiero; Antonio Mastropaolo; Luca Pascarella; Denys Poshyvanyk; Gabriele Bavota (ICSE, 2022)

Using Reinforcement Learning for Load Testing of Video Games. - Rosalia Tufano; Simone Scalabrino; Luca Pascarella; Emad Aghajani; Rocco Oliveto; Gabriele Bavota (ICSE, 2022)

To What Extent do Deep Learning-based Code Recommenders Generate Predictions by Cloning Code from the Training Set? - Matteo Ciniselli; Luca Pascarella; Gabriele Bavota (MSR, 2022)

An Empirical Study on the Usage of Transformer Models for Code Completion. - Matteo Ciniselli; Nathan Cooper; Luca Pascarella; Antonio Mastropaolo; Emad Aghajani; Denys Poshyvanyk; Massimiliano Di Penta; Gabriele Bavota (IEEE Trans. Software Eng., 2022)

Replication package for "An Empirical Study on the Usage of Transformer Models for Code Completion". - Matteo Ciniselli; Nathan Cooper; Luca Pascarella; Antonio Mastropaolo; Emad Aghajani; Denys Poshyvanyk; Massimiliano Di Penta; Gabriele Bavota (Zenodo, 2022)

Replication package for "An Empirical Study on the Usage of BERT Models for Code Completion". - Matteo Ciniselli; Nathan Cooper; Luca Pascarella; Denys Poshyvanyk; Massimiliano Di Penta; Gabriele Bavota (Zenodo, 2022)

Replication Package for: An Empirical Study on Code Comment Completion. - Antonio Mastropaolo; Emad Aghajani; Luca Pascarella; Gabriela Bavota (Zenodo, 2022)

Replication Package for: Using Deep Learning to Generate Complete Log Statements. - Antonio Mastropaolo; Luca Pascarella; Gabriele Bavota (Zenodo, 2022)

Replication package for "To What Extent do Deep Learning-based Code Recommenders Generate Predictions by Cloning Code from the Training Set? - Matteo Ciniselli; Luca Pascarella; Gabriele Bavota (Zenodo, 2022)

Microservice Logical Coupling: A Preliminary Validation. - Dario Amoroso d'Aragona; Luca Pascarella; Andrea Janes; Valentina Lenarduzzi; Davide Taibi 001 (ICSA-C, 2023)

Source Code Recommender Systems: The Practitioners' Perspective. - Matteo Ciniselli; Luca Pascarella; Emad Aghajani; Simone Scalabrino; Rocco Oliveto; Gabriele Bavota (ICSE, 2023)

On the Robustness of Code Generation Techniques: An Empirical Study on GitHub Copilot. - Antonio Mastropaolo; Luca Pascarella; Emanuela Guglielmi; Matteo Ciniselli; Simone Scalabrino; Rocco Oliveto; Gabriele Bavota (ICSE, 2023)

Automating Code-Related Tasks Through Transformers: The Impact of Pre-training. - Rosalia Tufano; Luca Pascarella; Gabriele Bavota (ICSE, 2023)

The NLBSE'23 Tool Competition. - Rafael Kallis; Maliheh Izadi; Luca Pascarella; Oscar Chaparro; Pooja Rani 001 (NLBSE@ICSE, 2023)

Grayscale and Event-Based Sensor Fusion for Robust Steering Prediction for Self-Driving Cars. - Luca Pascarella; Michele Magno (SAS, 2023)

Breaks and Code Quality: Investigating the Impact of Forgetting on Software Development. A Registered Report. - Dario Amoroso d'Aragona; Luca Pascarella; Andrea Janes; Valentina Lenarduzzi; Rafael Peñaloza; Davide Taibi 001 (CoRR, 2023)

On the Empirical Evidence of Microservice Logical Coupling. A Registered Report. - Dario Amoroso d'Aragona; Luca Pascarella; Andrea Janes; Valentina Lenarduzzi; Rafael Peñaloza; Davide Taibi 001 (CoRR, 2023)

Automated variable renaming: are we there yet? - Antonio Mastropaolo; Emad Aghajani; Luca Pascarella; Gabriele Bavota (Empir. Softw. Eng., 2023)

A comprehensive evaluation of SZZ Variants through a developer-informed oracle. - Giovanni Rosa; Luca Pascarella; Simone Scalabrino; Rosalia Tufano; Gabriele Bavota; Michele Lanza 001; Rocco Oliveto (J. Syst. Softw., 2023)

Towards Real-Time Fast Unmanned Aerial Vehicle Detection Using Dynamic Vision Sensors. - Jakub Mandula; Jonas Kühne; Luca Pascarella; Michele Magno (I2MTC, 2024)

Deep Learning-Based Code Completion: On the Impact on Performance of Contextual Information. - Matteo Ciniselli; Luca Pascarella; Gabriele Bavota (ICSME, 2024)

Towards Summarizing Code Snippets Using Pre-Trained Transformers. - Antonio Mastropaolo; Matteo Ciniselli; Luca Pascarella; Rosalia Tufano; Emad Aghajani; Gabriele Bavota (ICPC, 2024)

The NLBSE'24 Tool Competition. - Rafael Kallis; Giuseppe Colavito; Ali Al-Kaswan; Luca Pascarella; Oscar Chaparro; Pooja Rani 001 (NLBSE@ICSE, 2024)

Log statements generation via deep learning: Widening the support provided to developers. - Antonio Mastropaolo; Valentina Ferrari; Luca Pascarella; Gabriele Bavota (J. Syst. Softw., 2024)