# 商品数据清洗def clean_product_data(raw_data):    # 处理空值    raw_data.fillna({'stock':0}, inplace=True)    # 标准化价格格式    raw_data['price'] = raw_data['price'].apply(lambda x: float(x.strip('¥')))    # 去重    return raw_data.drop_duplicates('sku_id')

# 从API文档提取参数依赖关系def extract_relations(api_spec):    relations = []    for path in api_spec['paths']:        for method in api_spec['paths'][path]:            params = api_spec['paths'][path][method].get('parameters', [])            input_params = [p['name'] for p in params if p['in'] == 'body']            output_params = [api_spec['paths'][path][method]['responses']['200']['schema']['properties'].keys()]            relations.append((input_params, '触发', output_params))    return relations

// 商品节点CREATE (p:商品 {sku_id:'A001', name:'iPhone13', price:5999, stock:1000})// 促销节点CREATE (promo:促销 {id:'P100', type:'秒杀', start_time:'2023-11-01', discount:500})// 建立关系MATCH (p:商品 {sku_id:'A001'}), (promo:促销 {id:'P100'})CREATE (p)-[:参与促销]->(promo)

多维度测试属性标注：{  "节点类型": "订单",  "测试属性": [    {      "边界值": {        "max_items": 100,        "max_amount": 50000      }    },    {      "安全规则": [        "同IP高频下单检测",        "大额交易二次验证"      ]    },    {      "性能要求": {        "创建QPS": 1000,        "响应时间": "<500ms"      }    }  ]}

@pytest.mark.parametrize("coupon_type,user_level,payment,expected", test_matrix)def test_coupon_combinations(coupon_type, user_level, payment, expected):    # 初始化测试环境    user = create_user(level=user_level)    add_coupons(user, coupon_type)

    # 执行测试    result = place_order(user, payment)

    # 验证结果    assert result['status'] == expected

# 基于图谱生成的并发测试def test_inventory_concurrency():    # 获取测试商品    test_sku = get_node("商品", "sku_id", "A001")

    # 模拟100个并发请求    with ThreadPoolExecutor(max_workers=100) as executor:        futures = [executor.submit(place_order, test_sku) for _ in range(100)]

    # 验证库存一致性    final_stock = get_actual_stock(test_sku)    expected_stock = test_sku['stock'] - sum(f.result() for f in futures)    assert final_stock == expected_stock

1. 正向路径：   商品选择 → 关税计算 → 跨境支付 → 海关申报 → 物流发货

2. 异常路径：   - 关税计算失败 → 订单终止   - 支付金额与申报金额不一致 → 海关退单   - 物流信息超时未更新 → 自动退款

def generate_crossborder_data():    return {        "商品": {"price": 1500, "category": "电子产品"},        "用户": {"country": "US", "vip_level": "gold"},        "支付": {"amount": 1500, "currency": "USD"},        "预期关税": 300    }

def analyze_impact(changed_node):    # 1. 查找直接关联节点    direct_relations = get_relations(changed_node)    # 2. 查找间接关联节点    indirect_relations = []    for relation in direct_relations:        indirect_relations += get_relations(relation.target)    # 3. 关联测试用例    affected_cases = set()    for node in direct_relations + indirect_relations:        affected_cases.update(node.linked_cases)    return sorted(affected_cases)

# 基于历史数据的修复推荐def suggest_fixes(broken_case):    # 查找相似历史问题    similar_issues = search_historical_issues(        case_text=broken_case.text,        graph_context=get_subgraph(broken_case)    )

    # 推荐修复方案    return {        "recommended_fixes": [fix['solution'] for fix in similar_issues],        "confidence_score": calculate_confidence(similar_issues)    }