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cs.SE2026
Towards LLM-Enhanced Android Taint Analysis
Nicholas Miazzo, Marco Alecci, Jordan Samhi +2
Taint analysis is a fundamental technique for detecting sensitive data leaks in Android apps. However, traditional static tools, such as FlowDroid, still face well-known challenges…
cs.SE2025
GAPS: Targeted Execution of Android Apps via Static Path Reconstruction
Samuele Doria, Alexander Pilgun, Jordan Samhi +2
Targeted execution of Android applications (apps) remains a longstanding challenge for software testing and analysis. Although recent advances in GUI testing have substantially imp…
cs.SE2025
Evaluating LLM-Based Regression Test Generation
Jing Liu, Seongmin Lee, Eleonora Losiouk +1
Large Language Models (LLMs) have shown tremendous promise in automated software engineering. In this paper, we investigate LLMs for just-in-time regression test generation for pro…