AI辅助测试自动化框架设计：构建智能、高效的测试体系

传统测试自动化 → 挑战：维护成本高/适应性差/智能化程度低/覆盖率不足 → AI辅助测试自动化 → 优势：自动生成/自我修复/智能分析/优化效率/提升覆盖率

目录
├── 第一章：测试自动化框架的演进与挑战
├── 第二章：AI辅助测试自动化框架的核心概念与架构
├── 第三章：AI在测试脚本自动生成中的应用
├── 第四章：AI在测试脚本自我修复中的应用
├── 第五章：AI在测试数据智能管理中的应用
├── 第六章：AI在测试执行智能优化中的应用
├── 第七章：AI在测试结果智能分析中的应用
└── 第八章：实践案例与未来发展

脚本化测试 → 模块化测试框架 → 数据驱动测试框架 → 关键字驱动测试框架 → 混合驱动测试框架 → AI辅助测试自动化框架

传统测试自动化框架挑战分布：维护成本高(30%) | 适应性差(25%) | 智能化程度低(20%) | 覆盖率不足(15%) | 技术门槛高(10%)

AI技术 → 测试自动化框架变革 → 效率提升 → 成本降低 → 质量提高 → 价值实现

AI辅助测试自动化框架 = 传统测试自动化框架 + AI技术 + 智能决策系统 + 自适应机制

用户层 → API层 → 核心服务层 → 数据层 → 基础设施层
        ↓        ↓            ↓        ↓
      接口    业务逻辑        数据    计算资源

需求分析 → 测试设计 → 测试实现 → 测试执行 → 测试分析 → 反馈优化

import spacy
import re
import json
import os
from nltk.tokenize import sent_tokenize, word_tokenize
from nltk.corpus import stopwords
import random

# 确保中文显示正常
import matplotlib.pyplot as plt
plt.rcParams["font.family"] = ["SimHei", "WenQuanYi Micro Hei", "Heiti TC"]
plt.rcParams["axes.unicode_minus"] = False

# 加载中文NLP模型
try:
    nlp = spacy.load("zh_core_web_sm")
except:
    # 如果没有安装中文模型，下载并安装
    os.system("python -m spacy download zh_core_web_sm")
    nlp = spacy.load("zh_core_web_sm")

# 定义测试脚本模板
test_script_templates = {
    "web": {
        "login": "def test_login_{test_id}():
    # 测试目的: 验证{description}
    driver = webdriver.Chrome()
    driver.get('{url}')
    
    # 输入用户名
    driver.find_element(By.ID, '{username_id}').send_keys('{username_value}')
    # 输入密码
    driver.find_element(By.ID, '{password_id}').send_keys('{password_value}')
    # 点击登录按钮
    driver.find_element(By.ID, '{login_button_id}').click()
    
    # 验证登录成功
    try:
        success_element = WebDriverWait(driver, 10).until(
            EC.presence_of_element_located((By.ID, '{success_indicator_id}'))
        )
        assert success_element is not None
        print("登录测试通过")
    except Exception as e:
        print(f"登录测试失败: {str(e)}")
        assert False, "登录失败"
    finally:
        driver.quit()
",
        "search": "def test_search_{test_id}():
    # 测试目的: 验证{description}
    driver = webdriver.Chrome()
    driver.get('{url}')
    
    # 输入搜索关键词
    driver.find_element(By.ID, '{search_input_id}').send_keys('{search_keyword}')
    # 点击搜索按钮
    driver.find_element(By.ID, '{search_button_id}').click()
    
    # 验证搜索结果
    try:
        search_results = WebDriverWait(driver, 10).until(
            EC.presence_of_element_located((By.ID, '{search_results_id}'))
        )
        assert search_results is not None
        # 验证搜索结果包含关键词
        assert '{search_keyword}' in search_results.text
        print("搜索测试通过")
    except Exception as e:
        print(f"搜索测试失败: {str(e)}")
        assert False, "搜索失败"
    finally:
        driver.quit()
"
    },
    "api": {
        "get": "def test_get_api_{test_id}():
    # 测试目的: 验证{description}
    url = '{api_url}'
    headers = {headers}
    
    # 发送GET请求
    response = requests.get(url, headers=headers)
    
    # 验证响应状态码
    assert response.status_code == {expected_status_code}, f"期望状态码: {expected_status_code}, 实际状态码: {{response.status_code}}"
    
    # 验证响应数据
    try:
        data = response.json()
        # 验证关键字段存在
        for field in {required_fields}:
            assert field in data, f"响应数据中缺少字段: {{field}}"
        # 验证字段值符合预期
        {field_validations}
        print("GET API测试通过")
    except json.JSONDecodeError:
        print("响应不是有效的JSON格式")
        assert False, "响应格式错误"
    except AssertionError as e:
        print(f"数据验证失败: {{str(e)}}")
        assert False, "数据验证失败"
",
        "post": "def test_post_api_{test_id}():
    # 测试目的: 验证{description}
    url = '{api_url}'
    headers = {headers}
    data = {post_data}
    
    # 发送POST请求
    response = requests.post(url, headers=headers, json=data)
    
    # 验证响应状态码
    assert response.status_code == {expected_status_code}, f"期望状态码: {expected_status_code}, 实际状态码: {{response.status_code}}"
    
    # 验证响应数据
    try:
        response_data = response.json()
        # 验证关键字段存在
        for field in {required_fields}:
            assert field in response_data, f"响应数据中缺少字段: {{field}}"
        # 验证字段值符合预期
        {field_validations}
        print("POST API测试通过")
    except json.JSONDecodeError:
        print("响应不是有效的JSON格式")
        assert False, "响应格式错误"
    except AssertionError as e:
        print(f"数据验证失败: {{str(e)}}")
        assert False, "数据验证失败"
"
    }
}

# 需求解析函数
def parse_requirement(requirement_text):
    # 使用NLP处理需求文本
    doc = nlp(requirement_text)
    
    # 提取实体和关系
    entities = []
    relations = []
    
    for ent in doc.ents:
        entities.append((ent.text, ent.label_))
    
    # 提取关键词
    keywords = []
    stop_words = set(stopwords.words('chinese'))
    
    # 分词并过滤停用词
    words = word_tokenize(requirement_text)
    keywords = [word for word in words if word.isalnum() and word not in stop_words]
    
    # 识别测试类型
    test_type = "unknown"
    if any(keyword in requirement_text for keyword in ["登录", "Login", "login"]):
        test_type = "login"
    elif any(keyword in requirement_text for keyword in ["搜索", "Search", "search"]):
        test_type = "search"
    elif any(keyword in requirement_text for keyword in ["GET", "get", "获取"]):
        test_type = "get"
    elif any(keyword in requirement_text for keyword in ["POST", "post", "提交"]):
        test_type = "post"
    
    # 识别应用类型
    app_type = "web"
    if any(keyword in requirement_text for keyword in ["API", "接口", "api"]):
        app_type = "api"
    
    return {
        "entities": entities,
        "relations": relations,
        "keywords": keywords,
        "test_type": test_type,
        "app_type": app_type
    }

# 测试脚本生成函数
def generate_test_script(requirement_text, test_id=None):
    # 解析需求
    parsed_data = parse_requirement(requirement_text)
    
    # 如果没有提供test_id，生成一个随机ID
    if test_id is None:
        test_id = f"{random.randint(1000, 9999)}"
    
    # 获取对应的模板
    app_type = parsed_data["app_type"]
    test_type = parsed_data["test_type"]
    
    if app_type not in test_script_templates or test_type not in test_script_templates[app_type]:
        return f"错误: 不支持的应用类型 '{app_type}' 或测试类型 '{test_type}'"
    
    template = test_script_templates[app_type][test_type]
    
    # 根据测试类型填充模板
    if app_type == "web":
        if test_type == "login":
            script = template.format(
                test_id=test_id,
                description=requirement_text,
                url="https://example.com/login",
                username_id="username",
                username_value="test_user",
                password_id="password",
                password_value="test_password",
                login_button_id="login_button",
                success_indicator_id="welcome_message"
            )
        elif test_type == "search":
            # 从需求中提取搜索关键词
            search_keyword = "测试关键词"
            for keyword in parsed_data["keywords"]:
                if keyword not in ["搜索", "功能", "验证", "确保", "用户"]:
                    search_keyword = keyword
                    break
            
            script = template.format(
                test_id=test_id,
                description=requirement_text,
                url="https://example.com",
                search_input_id="search_input",
                search_keyword=search_keyword,
                search_button_id="search_button",
                search_results_id="search_results"
            )
    elif app_type == "api":
        if test_type == "get":
            script = template.format(
                test_id=test_id,
                description=requirement_text,
                api_url="https://api.example.com/users",
                headers="{'Content-Type': 'application/json', 'Authorization': 'Bearer token123'}",
                expected_status_code=200,
                required_fields=["id", "name", "email"],
                field_validations="# 可以根据实际需求添加更多字段验证"
            )
        elif test_type == "post":
            script = template.format(
                test_id=test_id,
                description=requirement_text,
                api_url="https://api.example.com/users",
                headers="{'Content-Type': 'application/json', 'Authorization': 'Bearer token123'}",
                post_data="{'name': 'Test User', 'email': 'test@example.com', 'password': 'password123'}",
                expected_status_code=201,
                required_fields=["id", "name", "email"],
                field_validations="# 可以根据实际需求添加更多字段验证"
            )
    
    # 添加必要的导入语句
    imports = "import unittest\nfrom selenium import webdriver\nfrom selenium.webdriver.common.by import By\nfrom selenium.webdriver.support.ui import WebDriverWait\nfrom selenium.webdriver.support import expected_conditions as EC\nimport requests\nimport json\n\n"
    if app_type == "api":
        imports = "import unittest\nimport requests\nimport json\n\n"
    
    # 添加类定义
    class_def = f"class Test{test_type.capitalize()}(unittest.TestCase):\n    \n"
    
    # 缩进测试方法
    indented_script = "    " + script.replace("\n", "\n    ")
    
    # 添加主函数
    main_function = "\n\nif __name__ == '__main__':\n    unittest.main()"
    
    # 组合完整的测试脚本
    complete_script = imports + class_def + indented_script + main_function
    
    return complete_script

# 保存测试脚本函数
def save_test_script(script, file_name):
    # 创建output目录（如果不存在）
    if not os.path.exists('output'):
        os.makedirs('output')
    
    # 保存脚本文件
    file_path = os.path.join('output', file_name)
    with open(file_path, 'w', encoding='utf-8') as f:
        f.write(script)
    
    print(f"测试脚本已保存到: {file_path}")
    return file_path

# 批量生成测试脚本函数
def batch_generate_test_scripts(requirements_file):
    # 读取需求文件
    with open(requirements_file, 'r', encoding='utf-8') as f:
        requirements = [line.strip() for line in f if line.strip()]
    
    # 批量生成测试脚本
    generated_scripts = []
    for i, requirement in enumerate(requirements):
        print(f"\n生成测试脚本 {i+1}/{len(requirements)}...")
        print(f"需求: {requirement}")
        
        # 生成测试脚本
        test_id = f"req_{i+1}"
        script = generate_test_script(requirement, test_id)
        
        # 保存测试脚本
        file_name = f"test_{test_id}.py"
        file_path = save_test_script(script, file_name)
        
        generated_scripts.append({
            "requirement": requirement,
            "file_path": file_path,
            "script": script
        })
    
    # 生成摘要报告
    report = {
        "total_requirements": len(requirements),
        "generated_scripts": len(generated_scripts),
        "scripts": generated_scripts
    }
    
    # 保存报告
    report_path = os.path.join('output', 'generation_report.json')
    with open(report_path, 'w', encoding='utf-8') as f:
        json.dump(report, f, ensure_ascii=False, indent=2)
    
    print(f"\n生成完成！共处理 {len(requirements)} 个需求，生成 {len(generated_scripts)} 个测试脚本")
    print(f"生成报告已保存到: {report_path}")
    
    return report

# 主函数
def main():
    print("===== AI辅助测试脚本自动生成工具 =====")
    
    # 示例需求
    sample_requirements = [
        "用户登录功能：验证用户输入正确的用户名和密码后可以成功登录系统",
        "搜索功能：验证用户在搜索框中输入关键词后可以找到相关结果",
        "用户信息API：验证GET请求可以获取用户列表数据",
        "创建用户API：验证POST请求可以成功创建新用户"
    ]
    
    # 保存示例需求到文件
    requirements_file = "sample_requirements.txt"
    with open(requirements_file, 'w', encoding='utf-8') as f:
        for req in sample_requirements:
            f.write(req + "\n")
    
    print(f"示例需求已保存到: {requirements_file}")
    
    # 批量生成测试脚本
    report = batch_generate_test_scripts(requirements_file)
    
    # 显示第一个生成的脚本示例
    if report["generated_scripts"] > 0:
        print("\n=== 生成的测试脚本示例 ===")
        print(report["scripts"][0]["script"][:500] + "...")
    
    print("\n工具使用说明：")
    print("1. 修改 sample_requirements.txt 文件，添加您的测试需求")
    print("2. 重新运行本工具，自动生成测试脚本")
    print("3. 在 output 目录中查看生成的测试脚本")

if __name__ == "__main__":
    main()

初始脚本 → 执行测试 → 收集反馈 → 分析结果 → 优化脚本 → 再次执行 → 持续优化

import cv2
import numpy as np
from selenium import webdriver
from selenium.webdriver.common.by import By
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.support import expected_conditions as EC
import os
import time
import difflib
import re

# 确保中文显示正常
import matplotlib.pyplot as plt
plt.rcParams["font.family"] = ["SimHei", "WenQuanYi Micro Hei", "Heiti TC"]
plt.rcParams["axes.unicode_minus"] = False

class UITestSelfHealing:
    def __init__(self):
        # 初始化WebDriver
        self.driver = webdriver.Chrome()
        self.driver.maximize_window()
        
        # 创建必要的目录
        self.screenshot_dir = "screenshots"
        self.element_dir = "elements"
        self.template_dir = "templates"
        self.healed_scripts_dir = "healed_scripts"
        
        for dir_path in [self.screenshot_dir, self.element_dir, self.template_dir, self.healed_scripts_dir]:
            if not os.path.exists(dir_path):
                os.makedirs(dir_path)
        
        # 设置元素匹配阈值
        self.matching_threshold = 0.7
        
        # 存储元素定位信息的映射
        self.element_locators = {}
        self.load_element_templates()
    
    def load_element_templates(self):
        """加载元素模板"""
        template_files = os.listdir(self.template_dir)
        for file in template_files:
            if file.endswith(".txt"):
                element_name = file[:-4]
                file_path = os.path.join(self.template_dir, file)
                with open(file_path, 'r', encoding='utf-8') as f:
                    locator_info = f.read().strip()
                    self.element_locators[element_name] = locator_info
    
    def save_element_template(self, element_name, locator_info):
        """保存元素模板"""
        file_path = os.path.join(self.template_dir, f"{element_name}.txt")
        with open(file_path, 'w', encoding='utf-8') as f:
            f.write(locator_info)
        self.element_locators[element_name] = locator_info
    
    def take_screenshot(self, name):
        """截取屏幕截图"""
        file_path = os.path.join(self.screenshot_dir, f"{name}.png")
        self.driver.save_screenshot(file_path)
        return file_path
    
    def capture_element(self, element, name):
        """捕获元素图像"""
        # 获取元素位置和大小
        location = element.location
        size = element.size
        
        # 截取整个页面的截图
        screenshot_path = self.take_screenshot(f"full_page_{name}")
        screenshot = cv2.imread(screenshot_path)
        
        # 计算元素在截图中的位置
        x = location['x']
        y = location['y']
        width = size['width']
        height = size['height']
        
        # 裁剪出元素图像
        element_image = screenshot[y:y+height, x:x+width]
        
        # 保存元素图像
        element_path = os.path.join(self.element_dir, f"{name}.png")
        cv2.imwrite(element_path, element_image)
        
        return element_path
    
    def find_element_by_image(self, element_name):
        """通过图像识别查找元素"""
        # 截取当前屏幕截图
        current_screenshot_path = self.take_screenshot(f"current_screen_{int(time.time())}")
        current_screenshot = cv2.imread(current_screenshot_path)
        
        # 加载元素模板图像
        template_path = os.path.join(self.element_dir, f"{element_name}.png")
        if not os.path.exists(template_path):
            print(f"错误: 元素模板 '{element_name}' 不存在")
            return None
        
        template = cv2.imread(template_path)
        
        # 使用模板匹配查找元素
        result = cv2.matchTemplate(current_screenshot, template, cv2.TM_CCOEFF_NORMED)
        min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(result)
        
        # 如果匹配度超过阈值，则认为找到了元素
        if max_val >= self.matching_threshold:
            print(f"找到元素 '{element_name}'，匹配度: {max_val:.2f}")
            # 计算元素中心位置
            h, w = template.shape[:2]
            center_x = max_loc[0] + w // 2
            center_y = max_loc[1] + h // 2
            return (center_x, center_y)
        else:
            print(f"未找到元素 '{element_name}'，最高匹配度: {max_val:.2f}")
            return None
    
    def click_element_by_coordinates(self, coordinates):
        """通过坐标点击元素"""
        if coordinates is not None:
            x, y = coordinates
            # 使用JavaScript模拟点击
            self.driver.execute_script(f"window.scrollTo(0, {y-100});") # 滚动到元素附近
            time.sleep(0.5) # 等待滚动完成
            self.driver.execute_script(f"document.elementFromPoint({x}, {y}).click();")
            return True
        return False
    
    def analyze_test_failure(self, exception):
        """分析测试失败原因"""
        exception_str = str(exception)
        print(f"测试失败: {exception_str}")
        
        # 分析失败类型
        failure_type = "unknown"
        if "NoSuchElementException" in exception_str:
            failure_type = "element_not_found"
        elif "StaleElementReferenceException" in exception_str:
            failure_type = "stale_element"
        elif "TimeoutException" in exception_str:
            failure_type = "timeout"
        
        return failure_type
    
    def heal_locator(self, element_name, failure_type):
        """修复元素定位器"""
        print(f"尝试修复元素 '{element_name}' 的定位器，失败类型: {failure_type}")
        
        # 尝试通过多种方式查找元素
        # 1. 尝试使用图像识别
        coordinates = self.find_element_by_image(element_name)
        if coordinates is not None:
            print(f"通过图像识别成功定位元素 '{element_name}'")
            # 点击元素
            self.click_element_by_coordinates(coordinates)
            
            # 获取该元素的新定位器
            try:
                # 使用JavaScript获取点击位置的元素
                element = self.driver.execute_script(
                    "return document.elementFromPoint(arguments[0], arguments[1]);", 
                    coordinates[0], coordinates[1]
                )
                
                # 尝试获取元素的ID、class等属性
                element_id = element.get_attribute("id")
                element_class = element.get_attribute("class")
                element_xpath = self.get_element_xpath(element)
                
                # 保存新的定位器信息
                new_locator = f"XPATH:{element_xpath}"
                if element_id:
                    new_locator = f"ID:{element_id}"
                elif element_class:
                    new_locator = f"CLASS:{element_class.split()[0]}" # 使用第一个class
                
                self.save_element_template(element_name, new_locator)
                print(f"已更新元素 '{element_name}' 的定位器: {new_locator}")
                
                return new_locator
            except Exception as e:
                print(f"获取新定位器时出错: {str(e)}")
                return None
        
        print(f"无法自动修复元素 '{element_name}' 的定位器")
        return None
    
    def get_element_xpath(self, element):
        """获取元素的XPath"""
        try:
            # 使用JavaScript获取元素的XPath
            xpath = self.driver.execute_script("""
                function getElementXPath(element) {
                    if (element.id !== '')
                        return 'id("' + element.id + '")';
                    if (element === document.body)
                        return element.tagName;
                    
                    var ix = 0;
                    var siblings = element.parentNode.childNodes;
                    for (var i = 0; i < siblings.length; i++) {
                        var sibling = siblings[i];
                        if (sibling === element)
                            return getElementXPath(element.parentNode) + '/' + element.tagName + '[' + (ix + 1) + ']';
                        if (sibling.nodeType === 1 && sibling.tagName === element.tagName)
                            ix++;
                    }
                }
                return getElementXPath(arguments[0]);
            """, element)
            return xpath
        except:
            return ""
    
    def heal_test_script(self, script_path, element_name, old_locator, new_locator):
        """修复测试脚本中的定位器"""
        # 读取原脚本
        with open(script_path, 'r', encoding='utf-8') as f:
            script_content = f.read()
        
        # 替换定位器
        locator_type, locator_value = old_locator.split(":", 1)
        new_locator_type, new_locator_value = new_locator.split(":", 1)
        
        # 构建替换模式
        # 例如: driver.find_element(By.ID, "username") -> driver.find_element(By.XPATH, "//input[@name='user']")
        old_pattern = f"find_element\(By\.{locator_type.upper()},\s*["']{locator_value}["']\)"
        new_pattern = f"find_element(By.{new_locator_type.upper()}, '{new_locator_value}')"
        
        # 使用正则表达式替换
        healed_content = re.sub(old_pattern, new_pattern, script_content)
        
        # 保存修复后的脚本
        script_name = os.path.basename(script_path)
        healed_script_path = os.path.join(self.healed_scripts_dir, f"healed_{script_name}")
        with open(healed_script_path, 'w', encoding='utf-8') as f:
            f.write(healed_content)
        
        print(f"已保存修复后的脚本到: {healed_script_path}")
        
        # 生成修复报告
        diff = difflib.unified_diff(
            script_content.splitlines(keepends=True),
            healed_content.splitlines(keepends=True),
            fromfile=script_path,
            tofile=healed_script_path
        )
        
        diff_report = ''.join(diff)
        diff_report_path = os.path.join(self.healed_scripts_dir, f"diff_{script_name}.txt")
        with open(diff_report_path, 'w', encoding='utf-8') as f:
            f.write(diff_report)
        
        print(f"已保存修复差异报告到: {diff_report_path}")
        
        return healed_script_path
    
    def run_test_with_healing(self, test_script_path):
        """运行测试并尝试自我修复"""
        print(f"\n===== 运行测试: {test_script_path} =====")
        
        # 首先尝试正常运行测试
        try:
            # 这里简化处理，实际应用中应该通过适当的方式运行测试脚本
            # 这里模拟测试失败的情况
            print("测试运行中...")
            time.sleep(2) # 模拟测试执行时间
            
            # 模拟一个NoSuchElementException异常
            raise Exception("模拟测试失败: selenium.common.exceptions.NoSuchElementException: Message: no such element")
            
            print("测试通过！不需要修复")
            return True
        except Exception as e:
            # 分析测试失败原因
            failure_type = self.analyze_test_failure(e)
            
            # 如果是元素未找到的错误，尝试修复
            if failure_type == "element_not_found":
                print("尝试进行自我修复...")
                
                # 假设我们知道是哪个元素出了问题
                # 实际应用中应该通过分析异常信息提取元素信息
                element_name = "login_button" # 示例元素名
                
                if element_name in self.element_locators:
                    old_locator = self.element_locators[element_name]
                    
                    # 打开测试页面
                    self.driver.get("https://example.com/login")
                    
                    # 尝试修复定位器
                    new_locator = self.heal_locator(element_name, failure_type)
                    
                    if new_locator:
                        # 修复测试脚本
                        healed_script_path = self.heal_test_script(
                            test_script_path, element_name, old_locator, new_locator
                        )
                        
                        print(f"自我修复成功！修复后的脚本: {healed_script_path}")
                        return True
                    else:
                        print("自我修复失败")
                        return False
                else:
                    print(f"元素 '{element_name}' 不在模板库中")
                    return False
            else:
                print(f"不支持的失败类型 '{failure_type}'，无法自动修复")
                return False
    
    def close(self):
        """关闭WebDriver"""
        self.driver.quit()

# 主函数
def main():
    print("===== UI测试自我修复工具 =====")
    
    # 创建自我修复实例
    self_healer = UITestSelfHealing()
    
    try:
        # 创建一个示例测试脚本文件
        sample_script = """import unittest
from selenium import webdriver
from selenium.webdriver.common.by import By
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.support import expected_conditions as EC

class TestLogin(unittest.TestCase):
    def setUp(self):
        self.driver = webdriver.Chrome()
        self.driver.get("https://example.com/login")
        self.driver.maximize_window()
    
    def test_login(self):
        # 输入用户名
        username_input = self.driver.find_element(By.ID, "username")
        username_input.send_keys("test_user")
        
        # 输入密码
        password_input = self.driver.find_element(By.ID, "password")
        password_input.send_keys("test_password")
        
        # 点击登录按钮 - 假设这个元素的定位器已经失效
        login_button = self.driver.find_element(By.ID, "login_button")  # 这里会失败
        login_button.click()
        
        # 验证登录成功
        WebDriverWait(self.driver, 10).until(
            EC.presence_of_element_located((By.ID, "welcome_message"))
        )
    
    def tearDown(self):
        self.driver.quit()

if __name__ == "__main__":
    unittest.main()
"""
        
        # 保存示例测试脚本
        sample_script_path = "sample_login_test.py"
        with open(sample_script_path, 'w', encoding='utf-8') as f:
            f.write(sample_script)
        
        print(f"已创建示例测试脚本: {sample_script_path}")
        
        # 创建一些示例元素模板
        print("创建示例元素模板...")
        self_healer.save_element_template("login_button", "ID:login_button")
        
        # 运行测试并尝试自我修复
        success = self_healer.run_test_with_healing(sample_script_path)
        
        if success:
            print("\n测试自我修复演示完成！")
            print("\n工具使用说明：")
            print("1. 在 templates 目录中创建元素定位器模板文件")
            print("2. 在 elements 目录中保存元素图像模板")
            print("3. 运行本工具，自动修复测试脚本中的定位器问题")
            print("4. 在 healed_scripts 目录中查看修复后的脚本")
        else:
            print("\n测试自我修复演示失败")
    finally:
        # 关闭WebDriver
        self_healer.close()

if __name__ == "__main__":
    main()

环境监测 → 变化识别 → 模式学习 → 脚本调整 → 效果验证 → 持续优化

数据收集 → 质量特征提取 → 质量模型训练 → 质量评估 → 质量报告 → 质量改进建议

隐私数据识别 → 隐私风险评估 → 脱敏策略制定 → 数据脱敏 → 脱敏效果评估 → 持续优化

测试需求分析 → 执行策略制定 → 执行顺序优化 → 并行执行优化 → 执行监控 → 执行调整 → 效果评估

异常检测 → 异常分类 → 异常诊断 → 异常处理 → 效果验证 → 知识积累

缺陷发现 → 缺陷分类 → 缺陷优先级确定 → 缺陷分配 → 缺陷跟踪 → 缺陷分析 → 缺陷预防

反馈收集 → 反馈分析 → 反馈分类 → 反馈优先级确定 → 反馈处理 → 反馈结果跟踪 → 反馈优化

需求分析 → 框架设计 → 模块开发 → 集成测试 → 试点应用 → 全面推广 → 持续优化

中心: AI辅助测试自动化框架未来
├── 趋势1: 全流程自动化
├── 趋势2: 自适应测试
├── 趋势3: 预测性测试
├── 趋势4: 多模态数据融合
├── 趋势5: 联邦学习与隐私保护
├── 趋势6: 可解释AI增强
└── 趋势7: AI与DevOps深度融合

AI辅助测试自动化框架的价值分布: 效率提升(35%) | 成本降低(25%) | 质量提高(20%) | 覆盖率提升(15%) | 体验改善(5%)