He has more than 100 publications with over 2000 citations. Recent publications cover topics such as a framework for repairing potentially vulnerable source code, automatically transforming legacy Python code to support structural pattern matching, a line-level explainable vulnerability detection approach for Java, a vulnerability introducing commit dataset for Java using an improved SZZ based approach, and IoT malware detection using machine learning.
Research Experience
He is the head of the Department of Software Engineering and an associate professor at the University of Szeged, Hungary. He has been leading several R&D projects related to quality assessment, improvement, and architecture reconstruction of software systems for major banks and software development companies in Hungary. Since 2005, he has served as Program Co-Chair and Program Committee member at major conferences in this field (ICSE, ICSME, ESEC/FSE, SANER, CSMR, WCRE, ICPC, SCAM, FASE, etc.).
Education
Habilitated doctor in Computer Sciences, 2015, University of Szeged; PhD in Mathematics and Computer Sciences (summa cum laude), 2005, University of Szeged; MSc - Computer Programmer Mathematician, 1997, Attila József University, Szeged; BSc - Computer Programmer Mathematician, 1995, Attila József University, Szeged.
Background
His research interests include static code analysis, metrics, quality assurance, design pattern and antipattern mining, and bug detection. He leads the Static Code Analysis group, which develops tools for analyzing the source code of various languages.
Miscellany
Teaching instructor for courses: IB202e - Programming I (BSc course: Object-oriented programming in Java); IMN103E - Advanced Programming (MSc course: Generic and generative programming in C++).