125 citations · 128 across the 6 of their papers we have counts for
7 papers
Newer and Bigger, but Safer? A Longitudinal Study of the Functionality-Security Gap in LLM-Generated Code
Thiago Santos de Moura, Fynn Matuschek, Flavio Toffalini +1
Large Language Models (LLMs) are widely used to generate code. Although their functional plausibility keeps improving, the generated code often contains security vulnerabilities. T…
ReproBreak: A Dataset of Reproducible Web Locator Breaks
Thiago Santos de Moura, Leon Adamietz, Samra Mehboob +1
Automated GUI testing frameworks such as Cypress and Playwright rely on locators to find and interact with web elements. A locator break occurs when a structural change in the appl…
Before Autonomy Takes Control: Software Testing in Robotics
Nils Chur, Thiago Santos de Moura, Argentina Ortega +4
Robotic systems are complex and safety-critical software systems. As such, they need to be tested thoroughly. Unfortunately, robot software is intrinsically hard to test compared t…
Designing for Novice Debuggers: A Pilot Study on an AI-Assisted Debugging Tool
Oka Kurniawan, Erick Chandra, Christopher M. Poskitt +3
Debugging is a fundamental skill that novice programmers must develop. Numerous tools have been created to assist novice programmers in this process. Recently, large language model…
Simulated Interactive Debugging
Yannic Noller, Erick Chandra, Srinidhi Chandrashekar +4
Debugging software, i.e., the localization of faults and their repair, is a key activity in software engineering. Therefore, effective and efficient debugging is one of the core sk…
VUDENC: Vulnerability Detection with Deep Learning on a Natural Codebase for Python
Laura Wartschinski, Yannic Noller, Thomas Vogel +2
Context: Identifying potential vulnerable code is important to improve the security of our software systems. However, the manual detection of software vulnerabilities requires expe…
Trust Enhancement Issues in Program Repair
Yannic Noller, Ridwan Shariffdeen, Xiang Gao +1
Automated program repair is an emerging technology that seeks to automatically rectify bugs and vulnerabilities using learning, search, and semantic analysis. Trust in automaticall…