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Valliappan Chidambaram Adaikkappan

Doctorat - McGill
Superviseur⋅e principal⋅e
David Meger
Sujets de recherche
Apprentissage par renforcement
Google Scholar
GitHub

Publications

CA2: Code-Aware Agent for Automated Game Testing
Valliappan Chidambaram Adaikkappan
Vincent Martineau
Joshua Romoff
David Meger
Automated game testing is important for verifying game functionality, but it remains a costly and time-consuming process. Manual testing oft… (voir plus)en misses edge cases, and current automated methods struggle to provide full code coverage. Prior work has explored reinforcement learning (RL) for game testing, but without leveraging internal code signals such as the call stack. We present Code Aware Agent (CA2), which uses call stack information to learn effective testing strategies. The agent receives the current function call trace along with the game state and learns to reach specific target functions. We instrument two types of environments, 1) State-based and 2) Image-based, with support for efficient call stack extraction. Through experimental evaluation, we find that CA2 achieves consistent improvement over the non-code aware baselines, which does not leverage call stack information. Our results show that incorporating code signals like the call stack enables more effective and targeted game testing.
2026-05-12
arXiv (prépublication)
doi.org
arxiv.org