Registered user since Wed 4 Mar 2020
Emanuele Iannone is a postdoctoral researcher in the Institute of Software Security (SoftSec) at the Hamburg University of Technology (TUHH), Germany. He earned a PhD in Computer Science in 2024 at the University of Salerno, Italy, defending a thesis on software vulnerability analysis, focusing on automated detection and assessment techniques, advised by Prof. Fabio Palomba. He is the principal Investigator of the DFG-funded project “SToCC: Security Testing of Code Components”. Previously, he was involved in the Horizon Europe project “Sec4AI4Sec” on automated vulnerability repair. He has been the co-organizing chair of SECUTE’26 and SECUTE’24 (https://secute-ws.github.io/), a workshop co-located with ASE’26 and EASE’24, respectively, which focused on the security testing of software systems. He has been a referee for prestigious international journals in software engineering (such as TSE, TOSEM, EMSE, and JSS). He has been involved in the program committees of several international conferences in software engineering (such as ASE, MSR, ICSME, and SANER). His research interests include software security testing, mining software repositories for security-related data, automated vulnerability repair, and vulnerability detection. His research also covers AI for Software Engineering, Software Analytics, Search-based Software Testing, Software Refactoring and Reengineering, and Program Comprehension. More info is at https://emaiannone.github.io/.
Contributions
2027
Mining Software Repositories
2026
SECUTE
ICSME
- Committee Member in Program Committee within the Industry Track-track
- Committee Member in Program Committee within the Replication and Negative Results-track
- Author of The Language of Security: How Prompt Syntax Shapes Secure Code Generation in Open LLMs within the Research Papers Track-track
- Committee Member in Program Committee within the Research Papers Track-track
- Author of VULTRITION: Nutrition Labels for Vulnerability Datasets within the Tool Demonstration and Data Showcase Track-track