David Nader-Palacio

According to our database, David Nader-Palacio authored at least 10 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of five.

2024

Which Syntactic Capabilities Are Statistically Learned by Masked Language Models for Code?

Alejandro Velasco, David N. Palacio, Daniel Rodríguez-Cárdenas, Denys Poshyvanyk

CoRR, 2024

2023

Using Transfer Learning for Code-Related Tasks.

Antonio Mastropaolo, Nathan Cooper, David Nader-Palacio, Simone Scalabrino, Denys Poshyvanyk, Rocco Oliveto, Gabriele Bavota

IEEE Trans. Software Eng., April, 2023

Evaluating and Explaining Large Language Models for Code Using Syntactic Structures.

David N. Palacio, Alejandro Velasco, Daniel Rodríguez-Cárdenas, Kevin Moran, Denys Poshyvanyk

CoRR, 2023

Toward a Theory of Causation for Interpreting Neural Code Models.

David N. Palacio, Nathan Cooper, Alvaro Rodriguez, Kevin Moran, Denys Poshyvanyk

CoRR, 2023

Benchmarking Causal Study to Interpret Large Language Models for Source Code.

Daniel Rodríguez-Cárdenas, David N. Palacio, Dipin Khati, Henry Burke, Denys Poshyvanyk

Proceedings of the IEEE International Conference on Software Maintenance and Evolution, 2023

2022

A Systematic Literature Review on the Use of Deep Learning in Software Engineering Research.

Cody Watson, Nathan Cooper, David Nader-Palacio, Kevin Moran, Denys Poshyvanyk

ACM Trans. Softw. Eng. Methodol., 2022

2021

Studying the Usage of Text-To-Text Transfer Transformer to Support Code-Related Tasks.

Antonio Mastropaolo, Simone Scalabrino, Nathan Cooper, David Nader-Palacio, Denys Poshyvanyk, Rocco Oliveto, Gabriele Bavota

Proceedings of the 43rd IEEE/ACM International Conference on Software Engineering, 2021

2020

Improving the effectiveness of traceability link recovery using hierarchical bayesian networks.

Kevin Moran, David N. Palacio, Carlos Bernal-Cárdenas, Daniel McCrystal, Denys Poshyvanyk, Chris Shenefiel, Jeff Johnson

Proceedings of the ICSE '20: 42nd International Conference on Software Engineering, Seoul, South Korea, 27 June, 2020

2019

Learning to Identify Security-Related Issues Using Convolutional Neural Networks.

David N. Palacio, Daniel McCrystal, Kevin Moran, Carlos Bernal-Cárdenas, Denys Poshyvanyk, Chris Shenefiel

Proceedings of the 2019 IEEE International Conference on Software Maintenance and Evolution, 2019

2018

Assessing single-objective performance convergence and time complexity for refactoring detection.

David Nader-Palacio, Daniel Rodríguez-Cárdenas, Jonatan Gómez

Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2018