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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.

Modelant provides JMI-compliant mechanism to read, process, export models in MOF 1.4, UML 1.3 and UML 1.4, including also an engine for generation of code (any texts) using Object-Oriented Programming and templates. It is an extensible framework allowing adding support of other languages, described using MOF 1.4 metamodels. Modelant provides Maven plugins to automate the creation and comparison of UML 1.3, UML 1.4, MOF 1.4 models; the generation of code from models; the reverse engineering of java code, relational databases and XML DTD/XSD; the transformatoion of models, e.g. tranformation of of UMl 1.3 models to UML 1.4; the comparison and change identification in UML 1.3/UML 1.4 models and MOF 1.4 metamodels. The produced UML 1.3 models are suitable to be imported in Rational Rose 2003 + XMI Plugin, WhiteStar UML / Star UML, Enterprise Architect, other, as they employ MOF 1.3/MOF 1.4 as reading MOF 1.3 is internally converted to MOF1.4 and XMI 1.1 and XMI 1.2. whereas the converted to UML 1.4 models can be imported in Argo UML, Enterprise Architect, other as they employ MOF 1.4 and XMI 1.1 and XMI 1.2. Modelant wraps the NetBeans Meta-Data Repository (MDR).

pact-jvm-consumer-groovy-v3 =========================== Groovy DSL for Pact JVM implementing V3 specification changes. ##Dependency The library is available on maven central using: * group-id = `au.com.dius` * artifact-id = `pact-jvm-consumer-groovy-v3_2.11` * version-id = `2.2.x` or `3.0.x` ##Usage Add the `pact-jvm-consumer-groovy-v3` library to your test class path. This provides a `PactMessageBuilder` class for you to use to define your pacts. If you are using gradle for your build, add it to your `build.gradle`: dependencies { testCompile 'au.com.dius:pact-jvm-consumer-groovy-v3_2.11:2.2.12' } ## Consumer test for a message consumer The `PactMessageBuilder` class provides a DSL for defining your message expectations. It works in much the same way as the `PactBuilder` class for Request-Response interactions. ### Step 1 - define the message expectations Create a test that uses the `PactMessageBuilder` to define a message expectation, and then call `run`. This will invoke the given closure with a message for each one defined in the pact. ```groovy def eventStream = new PactMessageBuilder().call { serviceConsumer 'messageConsumer' hasPactWith 'messageProducer' given 'order with id 10000004 exists' expectsToReceive 'an order confirmation message' withMetaData(type: 'OrderConfirmed') // Can define any key-value pairs here withContent(contentType: 'application/json') { type 'OrderConfirmed' audit { userCode 'messageService' } origin 'message-service' referenceId '10000004-2' timeSent: '2015-07-22T10:14:28+00:00' value { orderId '10000004' value '10.000000' fee '10.00' gst '15.00' } } } ``` ### Step 2 - call your message handler with the generated messages This example tests a message handler that gets messages from a Kafka topic. In this case the Pact message is wrapped as a Kafka `MessageAndMetadata`. ```groovy eventStream.run { Message message -> messageHandler.handleMessage(new MessageAndMetadata('topic', 1, new kafka.message.Message(message.contentsAsBytes()), 0, null, valueDecoder)) } ``` ### Step 3 - validate that the message was handled correctly ```groovy def order = orderRepository.getOrder('10000004') assert order.status == 'confirmed' assert order.value == 10.0 ``` ### Step 4 - Publish the pact file If the test was successful, a pact file would have been produced with the message from step 1.