质量评估

class FunctionalEvaluator:
    """功能质量评估器"""
    
    def evaluate(self, model: Model, 
                 test_cases: List[TestCase]) -> FunctionalReport:
        """
        功能质量评估
        
        评估项:
        1. 基准测试: 标准数据集表现
        2. 场景测试: 真实业务场景
        3. 边界测试: 极端输入
        4. 回归测试: 版本对比
        """
        # 基准测试
        benchmark_scores = self._run_benchmark(model)
        
        # 场景测试
        scenario_results = self._run_scenarios(model, test_cases)
        
        # 边界测试
        boundary_results = self._run_boundary_tests(model)
        
        # 回归测试
        regression_results = self._run_regression(model)
        
        return FunctionalReport(
            benchmark=benchmark_scores,
            scenarios=scenario_results,
            boundaries=boundary_results,
            regression=regression_results,
            overall_score=self._calculate_score(
                benchmark_scores, scenario_results,
                boundary_results, regression_results
            ),
        )

class PerformanceEvaluator:
    """性能评估器"""
    
    def evaluate(self, model: Model,
                 config: PerformanceConfig) -> PerformanceReport:
        """
        性能评估
        
        评估项:
        1. 基线性能: 默认配置
        2. 压力测试: 极限负载
        3. 并发测试: 多用户场景
        4. 弹性测试: 动态负载
        """
        report = PerformanceReport()
        
        # 基线性能
        report.baseline = self._baseline_test(model, config)
        
        # 延迟分析
        report.latency = self._latency_analysis(model, config)
        
        # 吞吐量测试
        report.throughput = self._throughput_test(model, config)
        
        # 压力测试
        report.stress = self._stress_test(model, config)
        
        # 资源分析
        report.resource_usage = self._resource_analysis(model, config)
        
        return report

class QualityScorecard:
    """质量评分卡"""
    
    def generate(self, evaluations: Dict[str, Report]) -> Scorecard:
        """
        综合质量评分卡
        
        权重:
        - 功能质量: 30%
        - 性能质量: 25%
        - 安全质量: 25%
        - 用户体验: 10%
        - 合规质量: 10%
        """
        weights = {
            'functional': 0.30,
            'performance': 0.25,
            'security': 0.25,
            'ux': 0.10,
            'compliance': 0.10,
        }
        
        scores = {
            'functional': evaluations['functional'].overall_score,
            'performance': evaluations['performance'].overall_score,
            'security': evaluations['security'].overall_score,
            'ux': evaluations['ux'].overall_score,
            'compliance': evaluations['compliance'].overall_score,
        }
        
        weighted_score = sum(
            s * w for s, w in zip(scores.values(), weights.values())
        )
        
        return Scorecard(
            overall=weighted_score,
            dimensions=scores,
            rating=self._map_to_rating(weighted_score),
            recommendations=self._generate_recommendations(
                evaluations
            ),
        )