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自愈测试流水线

使用 Synapse 记忆构建能从失败中学习并自动适应的测试流水线。


自愈测试流水线

传统测试套件在 UI 变化时会失败。自愈测试使用 Synapse 记忆从过往失败中学习并适应 — 减少不稳定测试与维护成本。

概念

┌─────────┐  失败   ┌──────────┐  存储   ┌──────────┐
│  测试   │ ───────▶ │ Synapse  │ ───────▶ │  记忆    │
│  运行   │          │  记忆    │          │ (失败)   │
└─────────┘          └──────────┘          └──────────┘
                           ▲                     │
                           │   回放              │
                           │  下次运行前         │
                           └─────────────────────┘
  1. 测试运行
  2. 若失败,存储失败信息(出了什么错、为什么、如何修)
  3. 下次运行:执行前回放相关失败
  4. 自动应用已知修复

实现

第 1 步:测试包装器

为每个测试包装记忆回放/存储:

import requests
from datetime import datetime

URL = "https://synapse.schaefer.zone"
MIND_KEY = "mk_..."

def self_healing_test(test_name, test_fn):
    """装饰器:用自愈记忆包装测试。"""
    def wrapper():
        # 1. 回放该测试的过往失败
        past_failures = requests.get(
            f"{URL}/memory/search?q={test_name}+failure",
            headers={"Authorization": f"Bearer {MIND_KEY}"}
        ).json()
        
        # 2. 在失败上下文中运行测试
        try:
            test_fn(known_failures=past_failures)
        except Exception as e:
            # 3. 存储失败
            store_failure(test_name, e, traceback.format_exc())
            raise
    
    return wrapper

def store_failure(test_name, error, traceback_str):
    requests.post(f"{URL}/memory",
        headers={"Authorization": f"Bearer {MIND_KEY}",
                 "Content-Type": "application/json"},
        json={
            "category": "mistake",
            "key": f"test_failure_{test_name}_{datetime.now().isoformat()}",
            "content": f"Test: {test_name}\nError: {error}\nTrace:\n{traceback_str}",
            "tags": ["test", "failure", test_name],
            "priority": "high"
        })

第 2 步:自适应测试逻辑

在测试内部检查已知失败并应用修复:

@self_healing_test
def test_login_page(browser, known_failures=None):
    browser.goto("https://app.com/login")
    
    # 检查是否之前见过这种页面变化
    if known_failures and known_failures.get("results"):
        for failure in known_failures["results"]:
            if "button moved" in failure["content"].lower():
                # 改用 accessibility 标签而非坐标
                browser.click(by_label="Login button")
                return
    
    # 默认:使用坐标
    browser.click(x=150, y=400)

第 3 步:恢复策略

把恢复策略作为记忆存储:

def store_recovery(failure_type, strategy):
    requests.post(f"{URL}/memory",
        headers={"Authorization": f"Bearer {MIND_KEY}",
                 "Content-Type": "application/json"},
        json={
            "category": "skill",
            "key": f"recovery_{failure_type}",
            "content": strategy,
            "tags": ["test", "recovery", failure_type],
            "priority": "high"
        })

# 为常见失败存储恢复策略
store_recovery("element_not_found",
    "When element not found by ID, try by CSS class, then by XPath, "
    "then by accessibility label. Take screenshot for debugging.")

store_recovery("timeout",
    "Increase timeout to 30s. If still fails, check if page is loading "
    "dynamically — wait for specific element instead of fixed time.")

store_recovery("stale_element",
    "Re-find element before each interaction. Don't cache element references "
    "across page transitions.")

第 4 步:CI 集成

# .gitlab-ci.yml
test:self-healing:
  script:
    - export SYNAPSE_MIND_KEY=$SYNAPSE_TEST_MIND_KEY
    - pytest tests/ --self-healing
  after_script:
    # 汇总新失败
    - python scripts/synapse_failure_summary.py

第 5 步:失败分析仪表板

# 获取最近一周的所有测试失败
r = requests.get(
    f"{URL}/memory/search?q=test+failure",
    headers={"Authorization": f"Bearer {MIND_KEY}"}
)

# 按测试名分组
failures = {}
for mem in r.json().get("results", []):
    test_name = extract_test_name(mem["content"])
    failures.setdefault(test_name, []).append(mem)

# 报告
for test, fails in sorted(failures.items(), key=lambda x: -len(x[1])):
    print(f"{test}: {len(fails)} failures")

最佳实践

常见失败模式存储

失败类型 存储内容
元素未找到 尝试的选择器、页面状态、截图
超时 等待时间、等待的对象
断言失败 期望值与实际值
网络错误 URL、状态码、响应体
权限被拒 所需权限、当前用户角色

下一步