stefanocarrera/autophagycode_D_he_train-mercury_Qwen3-0.6B_strategy_trust_t1_g7_metrics

该数据集是一个代码相关数据集，包含164个样本，仅用于训练。数据特征包括任务标识（task_id）、入口点（entry_point）、可执行状态（is_executable）、正确性（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（如词汇量、长度、体积、难度、努力和时间）、圈复杂度（cyclomatic_complexity）、维护性指数（maintainability_index）、代码行数（loc和sloc）、注释百分比（comment_percentage）、词汇多样性（TTR）、令牌字典（token_dict）、香农熵（shannon_entropy）、平均和最大预测熵（mean_predictive_entropy、max_predictive_entropy）、定义函数数量（n_func_defined）以及入口点重复性（entry_point_repeated）。这些特征用于评估代码质量、复杂度和可维护性，可能应用于编程教育、代码分析或自动化测试场景。

This dataset is a code-related dataset containing 164 samples, intended for training use only. The features include task identifier (task_id), entry point (entry_point), executable status (is_executable), correctness (is_correct), number of tests passed and failed (tests_passed, tests_failed), test run time (test_run_time_ms), error type (error_type), Halstead complexity metrics (such as vocabulary, length, volume, difficulty, effort, and time), cyclomatic complexity (cyclomatic_complexity), maintainability index (maintainability_index), lines of code (loc and sloc), comment percentage (comment_percentage), type-token ratio (TTR), token dictionary (token_dict), Shannon entropy (shannon_entropy), mean and maximum predictive entropy (mean_predictive_entropy, max_predictive_entropy), number of functions defined (n_func_defined), and entry point repetition (entry_point_repeated). These features are used to assess code quality, complexity, and maintainability, potentially applied in programming education, code analysis, or automated testing scenarios.