用AI自动构建云服务模拟器，解决手动开发效率低的问题。
Automated Synthesis of Cloud Emulators
- 结合大模型与符号规则，从云文档自动生成模拟器代码
- 在AWS和GCP服务上覆盖率达90%以上，准确率超LocalStack
- 适合云平台开发者、测试工程师快速搭建本地测试环境
DevOps编程（如使用CLI/API脚本或IaC框架）是管理云基础设施的关键。与传统编程不同，其测试需在真实云资源上执行，耗时、危险且成本高。云模拟器作为API级模拟工具，可在本地运行DevOps程序，但构建过程仍具挑战：需人工解读大量云文档并手动编写各服务、API及其交互逻辑，难以应对云服务复杂性与持续演进。CloudEmu是一种基于神经符号代码合成的自动化方法，通过结合大语言模型对文档的理解能力与云领域符号抽象，抑制幻觉、保障精度，同时利用真实云作为测试、修复与对齐的参照。评估显示，CloudEmu在主流云服务商（AWS与GCP）服务上具有高覆盖率与高准确性，优于由大型团队历时十年手工构建的领先工具LocalStack。
原文摘要 · Abstract (English)
DevOps programming (e.g., using CLI/API scripts or IaC frameworks) is key to cloud infrastructure management. Unlike traditional programming tasks, DevOps program testing needs provisioning and execution against actual cloud resources, which is often time-consuming, unsafe, and costly. Cloud emulators have gained popularity for easing DevOps program testing; they are generally API-level mocks that can execute DevOps programs in a local environment. Still, building these emulators remains challenging: developers must manually interpret extensive cloud documentation and handcraft logic for each service, API, and their interaction. This does not scale to the complexity of the cloud, which is further a moving target as the services and APIs evolve. CloudEmu is an automated approach that constructs emulators based on cloud documentation via neurosymbolic code synthesis. The key idea is to combine LLMs' general strengths in documentation understanding and code generation with cloud-specific symbolic abstractions that suppress hallucinations and enforce precision at scale, while using the real cloud as an oracle for automated testing, repair, and alignment. Our evaluation shows the effectiveness of CloudEmu on major cloud provider (AWS and GCP) services in both coverage and accuracy. CloudEmu outperforms the existing leading tool LocalStack, which was manually developed by a large team of engineers over a decade.
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