autophagycode_D_metrics_he_Qwen3-8B_lr0.0001_text_g6

该数据集包含164个训练样本，主要记录代码执行与分析相关的多维特征。数据结构包含16个字段：基础标识字段（task_id, entry_point）、执行状态字段（is_executable, is_correct, tests_passed/failed, test_run_time_ms, error_type）、代码复杂度指标（halstead_vocabulary/length/volume/difficulty/effort, maintainability_index）以及函数定义数量（n_func_defined）等。数据集未明确说明具体应用场景，但从字段构成推断适用于代码质量评估、程序错误检测或自动化测试等软件工程任务。数据以单一训练集形式存储，总大小20.2KB。

This dataset contains 164 training samples, which primarily record multi-dimensional features related to code execution and analysis. Its data structure includes 16 fields: basic identification fields (task_id, entry_point), execution status fields (is_executable, is_correct, tests_passed/failed, test_run_time_ms, error_type), code complexity metrics (Halstead vocabulary/length/volume/difficulty/effort, maintainability_index), and the count of defined functions (n_func_defined), among others. The specific application scenario of this dataset is not explicitly stated, but it can be inferred from the field composition that it is applicable to software engineering tasks such as code quality assessment, program bug detection, or automated testing. The dataset is stored as a single training set with a total size of 20.2 KB.