Rudolf Ferenc

Rudolf Ferenc

Szegedi Tudományegyetem

H-index: 33

Europe-Hungary

About Rudolf Ferenc

Rudolf Ferenc, With an exceptional h-index of 33 and a recent h-index of 19 (since 2020), a distinguished researcher at Szegedi Tudományegyetem, specializes in the field of Software Maintenance, Software Evolution, Software Quality, Software Engineering.

His recent articles reflect a diverse array of research interests and contributions to the field:

Known Vulnerabilities of Open Source Projects: Where Are the Fixes?

Assessing GPT-4-Vision's Capabilities in UML-Based Code Generation

Improved Bug Prediction Through Conceptual Metrics and Machine Learning= Továbbfejlesztett szoftverhiba előrejelzés fogalmi metrikák és gépi tanulás segítségével

A Comparative Study of Commit Representations for JIT Vulnerability Prediction

CrySyS dataset of CAN traffic logs containing fabrication and masquerade attacks

Is JavaScript Call Graph Extraction Solved Yet? A Comparative Study of Static and Dynamic Tools

IoT Malware Detection with Machine Learning

Don't DIY: Automatically transform legacy Python code to support structural pattern matching

Rudolf Ferenc Information

University

Position

Associate Professor

Citations(all)

5161

Citations(since 2020)

1583

Cited By

4377

hIndex(all)

33

hIndex(since 2020)

19

i10Index(all)

72

i10Index(since 2020)

35

Email

University Profile Page

Szegedi Tudományegyetem

Google Scholar

View Google Scholar Profile

Rudolf Ferenc Skills & Research Interests

Software Maintenance

Software Evolution

Software Quality

Software Engineering

Top articles of Rudolf Ferenc

Title

Journal

Author(s)

Publication Date

Known Vulnerabilities of Open Source Projects: Where Are the Fixes?

IEEE Security & Privacy

Antonino Sabetta

Serena Elisa Ponta

Rocio Cabrera Lozoya

Michele Bezzi

Tommaso Sacchetti

...

2024/1/5

Assessing GPT-4-Vision's Capabilities in UML-Based Code Generation

arXiv preprint arXiv:2404.14370

Gábor Antal

Richárd Vozár

Rudolf Ferenc

2024/4/22

Improved Bug Prediction Through Conceptual Metrics and Machine Learning= Továbbfejlesztett szoftverhiba előrejelzés fogalmi metrikák és gépi tanulás segítségével

Rudolf Ferenc

2024/1/26

A Comparative Study of Commit Representations for JIT Vulnerability Prediction

Computers

Tamás Aladics

Péter Hegedűs

Rudolf Ferenc

2024/1/11

CrySyS dataset of CAN traffic logs containing fabrication and masquerade attacks

Scientific Data

András Gazdag

Rudolf Ferenc

Levente Buttyán

2023/12/15

Is JavaScript Call Graph Extraction Solved Yet? A Comparative Study of Static and Dynamic Tools

IEEE Access

Gábor Antal

Péter Hegedűs

Zoltán Herczeg

Gábor Lóki

Rudolf Ferenc

2023/3/10

IoT Malware Detection with Machine Learning

ERCIM NEWS

Levente Buttyán

Rudolf Ferenc

2022

Don't DIY: Automatically transform legacy Python code to support structural pattern matching

Balázs Rózsa

Gábor Antal

Rudolf Ferenc

2022/10/3

An AST-Based Code Change Representation and Its Performance in Just-in-Time Vulnerability Prediction

Tamás Aladics

Péter Hegedűs

Rudolf Ferenc

2022/7/11

A Line-Level Explainable Vulnerability Detection Approach for Java

Balázs Mosolygó

Norbert Vándor

Péter Hegedűs

Rudolf Ferenc

2022/7/4

Static Call Graph Combination to Simulate Dynamic Call Graph Behavior

IEEE Access

Zoltán Ságodi

Edit Pengő

Judit Jász

István Siket

Rudolf Ferenc

2022/12/14

Static code analysis alarms filtering reloaded: A new real-world dataset and its ML-based utilization

IEEE Access

Péter Hegedűs

Rudolf Ferenc

2022/5/23

An End-to-End Framework for Repairing Potentially Vulnerable Source Code

Judit Jász

Péter Hegedűs

Ákos Milánkovich

Rudolf Ferenc

2022/10/3

A Vulnerability Introducing Commit Dataset for Java: An Improved SZZ based Approach

Tamás Aladics

Péter Hegedűs

Rudolf Ferenc

2022

Towards a prototype based explainable javascript vulnerability prediction model

Balázs Mosolygó

Norbert Vándor

Gábor Antal

Péter Hegedűs

Rudolf Ferenc

2021/3/27

Assessing ensemble learning techniques in bug prediction

Zsolt János Szamosvölgyi

Endre Tamás Váradi

Zoltán Tóth

Judit Jász

Rudolf Ferenc

2021/9/11

Bug prediction using source code embedding based on doc2vec

Tamás Aladics

Judit Jász

Rudolf Ferenc

2021/9/11

Bugsjs: a benchmark and taxonomy of javascript bugs

Software Testing, Verification And Reliability

Péter Gyimesi

Béla Vancsics

Andrea Stocco

Davood Mazinanian

Árpád Beszédes

...

2021/6

Improving vulnerability prediction of javascript functions using process metrics

arXiv preprint arXiv:2105.07527

Tamás Viszkok

Péter Hegedűs

Rudolf Ferenc

2021/5/16

An automatically created novel bug dataset and its validation in bug prediction

Journal of Systems and Software

Rudolf Ferenc

Péter Gyimesi

Gábor Gyimesi

Zoltán Tóth

Tibor Gyimóthy

2020/11/1

See List of Professors in Rudolf Ferenc University(Szegedi Tudományegyetem)