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This project is meant to simplyfy the usage of the excelent Configuration Admin and MetaType services for Felix OSGi. The bundle will create a service that allows other bundles to register an annotated interface. The ManagedProperties service will then create all the Metatype information, as well as ensuring that objects are cast to their right types. ManagedProperties also has a feature called Filters. A Filter is used to create an object, say a File, directly from a primitive Configuration Admin type. It can also contain logic, to allow the configuration to fail if, for example, a File doesn't exist.

According to Docker best practices a Docker container should not be up if the process fails to load properly. Apache Tomcat deploys all the web applications loaded in its webapp folder. This is a resilient solution for web applications not influencing the application server. However, In a Docker environment according to best practice, the process should fail in case the web application failed to initialize properly. By adding the additional jar created by this project to Tomcat classpath and adding the new listener in the Tomcat conf/server.xml the user can make sure the Tomcat process fails in case there is an initialization exception in their web application which will cause the Tomcat used the tomcat container to abort in immediately indicate that there was an initialization error Abort tomcat when a webapp fails to deploy in Docker container Docker container best practice. Tomcat does not stop if a webapp fail to deploy and the container will continue to run. By adding this listener the tomcat will abort in case the Tomcat fails to deploy the webapp, And the container will not start. You will need to place the listener in Tomcat server.xml and set the Tomcat classpath to contain this jar

DKPro Lab is a lightweight framework for parameter sweeping experiments. It allows to set up experiments consisting of multiple interdependent tasks in a declarative manner with minimal overhead. Parameters are injected into tasks using via annotated class fields. Data produced by a task for any particular parameter configuration is stored and re-used whenever possible to avoid the needless recalculation of results. Reports can be attached to each task to post-process the experimental results and present them in a convenient manner, e.g. as tables or charts.