问题描述
我终于运行了我的示例 dmn-quarkus 示例.是否有启用跟踪的属性，例如打印执行的决策序列?
I finally got my sample dmn-quarkus example running. Is there a property that enables the trace, such a way it prints the sequence of decisions executed?
我注意到，当我为 DMN 模型提供不正确的 JSON 时，Kogito 会以详细响应进行响应，告诉我哪个决定失败.
I noticed that when I provide a incorrect JSON for my DMN model, Kogito responds with a detail response, telling me which decision failed.
这太棒了！是否有一个属性可以打开以获取每个响应中的详细信息?
This is awesome! Is there a property to turn on to get the details in each response?
推荐答案
Kogito 基于域模型优先的代码生成方法
Kogito is based on a domain-model first approach to code generation
Kogito ergo 域
Kogito 采用您的业务领域，而不是相反 [...]
Kogito adopts to your business domain rather than the other way around [...]
这意味着自动代码生成的 API 将始终采用 DMN 模型的输入/输出上下文的形状"，而不再是通用 API 的 v7.x kie-server 方法.
this means the automatically code-generated API will always take the "shape" of the input/output context of the DMN model, and no longer the v7.x kie-server approach of a generic API.
您在错误期间获得的信息旨在提供类似于堆栈跟踪的信息.
The information you obtain during error is meant to provide an analogous to a stacktrace.
您始终可以利用 Kogito API 编程模型自己构建 REST 服务，以更好地满足您的特定业务需求的方式 -- 应提供 DMNDecisionResult(s) 列表.例如，一种务实的方法可能是检查自动生成的代码，然后根据此代码编写定制服务.
You can always leverage the Kogito API programming model to build the REST service yourself, in the way better fit your specific business requirement --shall that be provide a list of DMNDecisionResult(s). For instance a pragmatic approach could be to inspect the automatically generated code, and then code a bespoke service, based on this one.
我们正在研究审计功能要求，但目前还没有提供现成的.我们始终欢迎社区反馈，尤其是在这个非常早期的版本中！不要犹豫，加入我们社区.google.com/d/forum/kogito-development" rel="nofollow noreferrer">邮件列表 或提出 JIRA 票 参与对话，考虑到社区反馈和建议，团队很乐意进一步研究它！
We are looking into Audit functional requirements, but that is not provided out of the box yet. We always welcome community feedback, especially even more in this very early versions! Don't hesitate to join the community on our mailing-list or raise a JIRA ticket to take part of the conversation, the team will be glad to look further into it considering community feedback and suggestions!
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