CoverageEval

该数据集名为COVERAGEEVAL，旨在评估大型语言模型（LLM）在代码覆盖率预测任务上的表现。它是通过执行HumanEval数据集中的测试用例并收集代码覆盖率信息而创建的。该数据集保留了HumanEval数据集的结构，并为每个测试用例增加了覆盖率注释，从而为评估LLM提供了一个标准化的基准。其所涉及的任务是代码覆盖率预测。

This dataset, named COVERAGEEVAL, is designed to evaluate the performance of Large Language Models (LLMs) on the code coverage prediction task. It was developed by executing the test cases from the HumanEval dataset and collecting corresponding code coverage information. This dataset retains the structural framework of the original HumanEval dataset, while adding coverage annotations to each test case, thus providing a standardized benchmark for LLM evaluation. The task addressed by this dataset is code coverage prediction.