Optimizing and maintaining up-to-date API documentation is a challenging problem for evolving OpenAPIs. In this poster, we propose a data-driven continuous optimization solution and multilingual SDK generation scheme to improve the comprehensibility of API documentation. We compute the correlation between API integrity and API trial success rate. Based on this, we partition the API to ensure that each API has a correct optimization direction. Then, we propose a fine-grained(i.e., parameter level) continuous optimization solution to annotate problems in API documents in real-time. Based on the above resolutions, we can provide theoretical analysis and support for the optimization and management of API documents. Finally, we explore the crucial challenges of OpenAPIs and introduce a tailored solution, TeaDSL, a multi-language SDK solution for all OpenAPI gateways. TeaDSL is a domain-specific language that expresses OpenAPI gateways, generating SDKs, code samples, and test cases. The experiments evaluated on the online system show that this work's approach significantly improves the user experience of learning OpenAPIs.

翻译：优化和维护API文档的实时更新对于不断演进的OpenAPI来说是一项具有挑战性的问题。在本海报中，我们提出了一种数据驱动的持续优化方案及多语言SDK生成策略，旨在提升API文档的可理解性。我们计算API完整性与API试调用成功率之间的相关性，据此对API进行划分，确保每个API拥有正确的优化方向。随后，我们提出一种细粒度（即参数级别）的持续优化方案，用于实时标注API文档中的问题。基于上述解决方案，我们能够为API文档的优化与管理提供理论分析与支持。最后，我们探讨了OpenAPI面临的关键挑战，并引入了一套定制化解决方案——TeaDSL，这是一种面向所有OpenAPI网关的多语言SDK方案。TeaDSL是一种领域特定语言，可表达OpenAPI网关，并生成SDK、代码示例及测试用例。在线系统上的实验评估表明，本工作的方法显著提升了用户学习OpenAPI的体验。