autophagycode_D_metrics_he_Qwen3-14B_lr0.0001_text_g4

该数据集包含与编程任务相关的信息，主要用于代码执行、测试结果分析及代码复杂度评估。数据集包含多个特征字段，包括任务ID（task_id）、入口点（entry_point）、是否可执行（is_executable）、是否正确（is_correct）、通过和失败的测试数量（tests_passed, tests_failed）、测试运行时间（test_run_time_ms）、错误类型（error_type）、Halstead复杂度指标（halstead_vocabulary, halstead_length, halstead_volume, halstead_difficulty, halstead_effort）、可维护性指数（maintainability_index）、定义的函数数量（n_func_defined）以及入口点是否重复（entry_point_repeated）。数据集分为一个训练集（train），包含164个样本，总大小为20123字节。适用于代码质量分析、自动化测试和程序复杂度研究等场景。This dataset contains information related to programming tasks, primarily used for code execution, test result analysis, and code complexity evaluation. The dataset includes multiple feature fields, such as task ID (task_id), entry point (entry_point), executability status (is_executable), correctness status (is_correct), number of passed and failed tests (tests_passed, tests_failed), test runtime (test_run_time_ms), error type (error_type), Halstead complexity metrics (halstead_vocabulary, halstead_length, halstead_volume, halstead_difficulty, halstead_effort), maintainability index (maintainability_index), number of defined functions (n_func_defined), and whether the entry point is repeated (entry_point_repeated). The dataset is split into one training set (train), which contains 164 samples with a total size of 20123 bytes. It is applicable to scenarios such as code quality analysis, automated testing, and program complexity research.