AI RESEARCH
DuET: Dual Execution for Test Output Prediction with Generated Code and Pseudocode
arXiv CS.CL
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ArXi:2604.11514v1 Announce Type: cross This work addresses test output prediction, a key challenge in test case generation. To improve the reliability of predicted outputs by LLMs, prior approaches generate code first to ground predictions. One grounding strategy is direct execution of generated code, but even minor errors can cause failures. To address this, we