REPOEXEC: Evaluate Code Generation with a Repository-Level Executable Benchmark

The ability of CodeLLMs to generate executable and functionally correct code at the \textit{repository-level scale }remains largely unexplored. We introduce \methodnamews, a novel benchmark for evaluating code generation at the repository-level scale, emphasizing executability and correctness. \methodnamews provides an automated system that verifies requirements and incorporates a mechanism for dynamically generating high-coverage test cases to assess the functionality of generated code. Our work explores a controlled scenario where developers specify necessary code dependencies, challenging the model to integrate these accurately. Experiments show that while pretrained LLMs outperform instruction-tuning models in correctness, the latter excel in utilizing provided dependencies and demonstrating debugging capabilities. \methodnamews aims to provide a comprehensive evaluation of code functionality and alignment with developer intent, paving the way for more reliable and applicable CodeLLMs in real-world scenarios.