Rohit Gheyi

LLMs misclassify non-equivalent code as equivalent, with performance deteriorating on more complex tasks and showing unexpected language-specific biases.

While loops and list comprehensions can double cognitive load for novice developers compared to for loops, revealing critical insights for code comprehension and maintainability.

Identifying 13 distinct bugs in Python refactoring implementations reveals significant gaps in current automated tools that could jeopardize software reliability.

AI-driven interviews achieved a 90.9% positive experience rating, but raised concerns about depth and privacy that could redefine ESE methodologies.