We present a comprehensive evaluation of Large Language Models (LLMs) on Computer Science (CS) Data Structure examination questions. Our work introduces a new benchmark dataset comprising exam questions from Tel Aviv University (TAU), curated to assess LLMs' abilities in handling closed and multiple-choice questions. We evaluated the performance of OpenAI's GPT 4o and Anthropic's Claude 3.5, popular LLMs, alongside two smaller LLMs, Mathstral 7B and LLaMA 3 8B, across the TAU exams benchmark. Our findings provide insight into the current capabilities of LLMs in CS education.
@article{arxiv.2604.23347,
title = {Evaluating Large Language Models on Computer Science University Exams in Data Structures},
author = {Edan Gabay and Yael Maoz and Jonathan Stahl and Naama Maoz and Abdo Amer and Orr Eilat and Hanoch Levy and Michal Kleinbort and Amir Rubinstein and Adi Haviv},
journal= {arXiv preprint arXiv:2604.23347},
year = {2026}
}