标题： 企业 Protobuf 系统的自动化测试数据生成：一种增强型统计方法 显示英文标题

标题： Automated Test Data Generation for Enterprise Protobuf Systems: A Metaclass-Enhanced Statistical Approach

摘要： 大规模企业系统利用协议缓冲区（protobuf）在性能测试方面提出了重大挑战，特别是在针对具有复杂嵌套数据结构的中间业务接口时。 传统的测试数据生成方法无法处理企业protobuf模式中固有的复杂层次结构和图状结构。 本文提出了一种新的测试数据生成框架，该框架利用Python的元类系统进行动态类型增强，并利用生产日志的统计分析来提取真实的值域。 我们的方法结合了自动模式内省、统计值分布分析以及递归下降算法来处理深度嵌套结构。 在三个真实企业系统的实验评估表明，与现有方法相比，测试数据准备时间减少了高达95%，测试覆盖率提高了80%。 该框架成功处理了最多15层嵌套的protobuf结构，并在几秒钟内生成包含超过100,000个测试用例的全面测试套件。 显示英文摘要

摘要： Large-scale enterprise systems utilizing Protocol Buffers (protobuf) present significant challenges for performance testing, particularly when targeting intermediate business interfaces with complex nested data structures. Traditional test data generation approaches are inadequate for handling the intricate hierarchical and graph-like structures inherent in enterprise protobuf schemas. This paper presents a novel test data generation framework that leverages Python's metaclass system for dynamic type enhancement and statistical analysis of production logs for realistic value domain extraction. Our approach combines automatic schema introspection, statistical value distribution analysis, and recursive descent algorithms for handling deeply nested structures. Experimental evaluation on three real-world enterprise systems demonstrates up to 95\% reduction in test data preparation time and 80\% improvement in test coverage compared to existing approaches. The framework successfully handles protobuf structures with up to 15 levels of nesting and generates comprehensive test suites containing over 100,000 test cases within seconds.