José D'Abruzzo Pereira

Orcid: 0000-0003-0717-3396

According to our database1, José D'Abruzzo Pereira authored at least 12 papers between 2019 and 2023.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of five.

Timeline

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Bibliography

2023
A Model-Driven Approach for the Management and Enforcement of Coding Conventions.
IEEE Access, 2023

An Approach to Characterize the Security of Open-Source Functions using LSP.
Proceedings of the 34th IEEE International Symposium on Software Reliability Engineering, 2023

2022
A Software Vulnerability Dataset of Large Open Source C/C++ Projects.
Proceedings of the 27th IEEE Pacific Rim International Symposium on Dependable Computing, 2022

On the use of the TMA Framework to promote self-adaptation capabilities in TalkConnect.
Proceedings of the 11th Latin-American Symposium on Dependable Computing, 2022

On the Use of Deep Graph CNN to Detect Vulnerable C Functions.
Proceedings of the 11th Latin-American Symposium on Dependable Computing, 2022

2021
Characterizing Buffer Overflow Vulnerabilities in Large C/C++ Projects.
IEEE Access, 2021

On Building a Vulnerability Dataset with Static Information from the Source Code.
Proceedings of the 10th Latin-American Symposium on Dependable Computing, 2021

Machine Learning to Combine Static Analysis Alerts with Software Metrics to Detect Security Vulnerabilities: An Empirical Study.
Proceedings of the 17th European Dependable Computing Conference, 2021

2020
Techniques and Tools for Advanced Software Vulnerability Detection.
Proceedings of the 2020 IEEE International Symposium on Software Reliability Engineering Workshops, 2020

A platform to enable self-adaptive cloud applications using trustworthiness properties.
Proceedings of the SEAMS '20: IEEE/ACM 15th International Symposium on Software Engineering for Adaptive and Self-Managing Systems, Seoul, Republic of Korea, 29 June, 2020

On the Use of Open-Source C/C++ Static Analysis Tools in Large Projects.
Proceedings of the 16th European Dependable Computing Conference, 2020

2019
An Exploratory Study on Machine Learning to Combine Security Vulnerability Alerts from Static Analysis Tools.
Proceedings of the 9th Latin-American Symposium on Dependable Computing, 2019


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