{"repo": "bosswnx/deeplearning-course-nju", "files": {"run.sh": {"5da492c448b6b8005e878de1bf5fe72ca722a260": {"t": 1785745950.3447845, "n": 5179, "h": "e4f50d51783d7f98", "c": "#!/bin/bash\n# ============================================================\n# LLM-APR 实验一键运行脚本\n#\n# 使用前请确保:\n#   1. 已安装 Defects4J 并添加到 PATH\n#   2. 已安装 Java 8\n#   3. 已设置 DEEPSEEK_API_KEY 环境变量\n#   4. 已安装 Python 依赖: pip install -r requirements.txt\n#\n# 用法:\n#   # 完整运行（提取数据 + 三种策略全部运行）\n#   bash run.sh full\n#\n#   # 仅提取缺陷数据\n#   bash run.sh extract\n#\n#   # 快速测试（仅取 5 个缺陷 × basic 策略，验证流程能跑通）\n#   bash run.sh quick\n#\n#   # 仅运行实验（已有 bugs.json）\n#   bash run.sh experiment\n#\n#   # 仅分析结果\n#   bash run.sh analyze\n# ============================================================\n\nset -e\n\nSCRIPT_DIR=\"$(cd \"$(dirname \"$0\")\" && pwd)\"\ncd \"$SCRIPT_DIR\"\n\n# 颜色输出\nRED='\\033[0;31m'\nGREEN='\\033[0;32m'\nYELLOW='\\033[1;33m'\nNC='\\033[0m'\n\ninfo()  { echo -e \"${GREEN}[INFO]${NC} $1\"; }\nwarn()  { echo -e \"${YELLOW}[WARN]${NC} $1\"; }\nerror() { echo -e \"${RED}[ERROR]${NC} $1\"; exit 1; }\n\n# ==================== 环境检查 ====================\ncheck_env() {\n    info \"检查运行环境...\"\n\n    # Java\n    if ! command -v java &>/dev/null; then\n        error \"Java not found! 请安装 JDK 1.8\"\n    fi\n    java_version=$(java -version 2>&1 | head -1)\n    info \"Java: $java_version\"\n\n    # Python\n    if ! command -v python3 &>/dev/null; then\n        error \"Python3 not found!\"\n    fi\n    python_version=$(python3 --version)\n    info \"Python: $python_version\"\n\n    # Defects4J\n    if ! command -v defects4j &>/dev/null; then\n        if [ -n \"$DEFECTS4J_HOME\" ] && [ -f \"$DEFECTS4J_HOME/framework/bin/defects4j\" ]; then\n            export PATH=\"$PATH:$DEFECTS4J_HOME/framework/bin\"\n            info \"Defects4J found at: $DEFECTS4J_HOME\"\n        else\n            error \"Defects4J not found!\\n  请安装: git clone https://github.com/rjust/defects4j && cd defects4j && ./init.sh\\n  然后: export PATH=\\$PATH:\\$(pwd)/framework/bin\"\n        fi\n    else\n        info \"Defects4J: $(which defects4j)\"\n    fi\n\n    # API Key\n    if [ -z \"$DEEPSEEK_API_KEY\" ]; then\n        error \"DEEPSEEK_API_KEY not set!\\n  请运行: export DEEPSEEK_API_KEY='your_key_here'\"\n    fi\n    info \"DEEPSEEK_API_KEY: ***$(echo $DEEPSEEK_API_KEY | tail -c 5)\"\n\n    # Python 依赖\n    python3 -c \"import openai, tqdm\" 2>/dev/null || {\n        warn \"缺少 Python 依赖，正在安装...\"\n        pip install -r requirements.txt\n    }\n\n    info \"环境检查通过!\"\n    echo \"\"\n}\n\n# ==================== 步骤 1: 提取缺陷数据 ====================\ndo_extract() {\n    info \"========== 步骤 1: 提取缺陷数据 ==========\"\n\n    if [ -f \"data/bugs.json\" ]; then\n        count=$(python3 -c \"import json; print(len(json.load(open('data/bugs.json'))))\")\n        warn \"data/bugs.json 已存在 ($count 个缺陷), 跳过提取\"\n        warn \"如需重新提取，请先删除 data/bugs.json\"\n        return\n    fi\n\n    # 可以通过 --max-per-project 控制数量，快速测试时用 5\n    extra_args=\"\"\n    if [ \"$1\" = \"quick\" ]; then\n        extra_args=\"--projects Chart Lang Math --max-per-project 5\"\n        info \"快速模式: 仅提取 Chart/Lang/Math 各 5 个缺陷\"\n    fi\n\n    python3 scripts/extract_bugs.py --output data/bugs.json $extra_args\n\n    count=$(python3 -c \"import json; print(len(json.load(open('data/bugs.json'))))\")\n    info \"提取完成: $count 个缺陷 -> data/bugs.json\"\n    echo \"\"\n}\n\n# ==================== 步骤 2: 运行实验 ====================\ndo_experiment() {\n    info \"========== 步骤 2: 运行实验 ==========\"\n\n    if [ ! -f \"data/bugs.json\" ]; then\n        error \"data/bugs.json 不存在! 请先运行: bash run.sh extract\"\n    fi\n\n    strategy=\"${1:-all}\"\n    limit_arg=\"\"\n    if [ -n \"$2\" ]; then\n        limit_arg=\"--limit $2\"\n    fi\n\n    info \"策略: $strategy\"\n    python3 scripts/run_experiment.py \\\n        --bugs data/bugs.json \\\n        --strategy \"$strategy\" \\\n        --output results/ \\\n        $limit_arg\n\n    info \"实验完成! 结果保存在 results/ 目录\"\n    echo \"\"\n}\n\n# ==================== 步骤 3: 分析结果 ====================\ndo_analyze() {\n    info \"========== 步骤 3: 分析结果 ==========\"\n\n    if [ ! -d \"results\" ]; then\n        error \"results/ 目录不存在! 请先运行实验\"\n    fi\n\n    python3 scripts/analyze_results.py \\\n        --results-dir results/ \\\n        --output results/analysis.md\n\n    info \"分析报告: results/analysis.md\"\n    echo \"\"\n}\n\n# ==================== 主入口 ====================\ncase \"${1:-help}\" in\n    full)\n        check_env\n        do_extract\n        do_experiment \"all\"\n        do_analyze\n        info \"全部完成!\"\n        ;;\n    quick)\n        check_env\n        do_extract \"quick\"\n        do_experiment \"basic\" \"\"\n        do_analyze\n        info \"快速测试完成! 请查看 results/analysis.md\"\n        ;;\n    extract)\n        check_env\n        do_extract \"${2:-}\"\n        ;;\n    experiment)\n        check_env\n        do_experiment \"${2:-all}\" \"${3:-}\"\n        ;;\n    analyze)\n        do_analyze\n        ;;\n    help|*)\n        echo \"\"\n        echo \"LLM-APR 实验运行脚本\"\n        echo \"\"\n        echo \"用法: bash run.sh <command>\"\n        echo \"\"\n        echo \"命令:\"\n        echo \"  full        完整运行 (提取 + 实验 + 分析)\"\n        echo \"  quick       快速测试 (15个缺陷 × basic策略)\"\n        echo \"  extract     仅提取缺陷数据\"\n        echo \"  experiment  仅运行实验 [strategy] [limit]\"\n        echo \"              e.g. bash run.sh experiment basic 10\"\n        echo \"  analyze     仅分析结果\"\n        echo \"  help        显示此帮助\"\n        echo \"\"\n        echo \"环境变量:\"\n        echo \"  DEEPSEEK_API_KEY    DeepSeek API密钥 (必须)\"\n        echo \"  DEFECTS4J_HOME      Defects4J安装目录\"\n        echo \"\"\n        ;;\nesac\n"}}}}