stefanocarrera/autophagycode_D_he_train-mercury_Qwen3-0.6B_strategy_trust_t1_g8_metrics

该数据集包含代码相关任务的元数据，用于分析代码质量和执行结果。特征包括任务ID、入口点、可执行性、正确性、测试通过/失败数、测试运行时间、错误类型、Halstead复杂度指标（如词汇量、长度、体积、难度、努力程度、时间）、圈复杂度、可维护性指数、代码行数（LOC和SLOC）、注释百分比、TTR（类型-标记比率）、标记字典、香农熵、预测熵（均值和最大值）、定义函数数量以及入口点重复标志。数据集分为训练集，包含164个样本，总大小约240KB，下载大小约104KB。This dataset contains metadata for code-related tasks, which is used for analyzing code quality and execution outcomes. Its features include task ID, entry point, executability, correctness, number of passed/failed tests, test runtime, error type, Halstead complexity metrics (such as vocabulary, length, volume, difficulty, effort, and time), cyclomatic complexity, maintainability index, lines of code (LOC and SLOC), comment percentage, TTR (Type-Token Ratio), token dictionary, Shannon entropy, predictive entropy (mean and maximum value), number of defined functions, and entry point duplication flag. The dataset is split into a training set containing 164 samples, with a total size of approximately 240 KB and a download size of approximately 104 KB.