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Easy to install library for adding dynamic display, control and configuration of java.util.logging to any swing based application. Useful for debugging apps in production situations; can interactively configure logging while an application is running including adding a handler to save logging output to a file. Changes made to an application's default/startup logging can be saved and automatically applied at startup. LogMan "single" library package for use in swing apps. The jar can be executed, "java -jar xxx", for a demo of the library. See com.raelity.logman.demo.Main for an example of adding the library to a swing app.

Nuun Kernel is a software kernel for framework creation. It brings a powerful plugin design plus a JSR 330 compliant injection mechanism backed by Guice. Plugin benefits from kernel capabilities by sending requests to it : - kernel params request : - Classpath scans request :on class by name, annotation, meta annotation or more generally Predicate - Binding Request : Nuun Kernel provides an SPI in order to bring IOC from other vendors. Nuun Kernel come with 2 plugins: - Configuration Plugin : a plugin that inject the good property based on @Property annotation. - Log plugin : a Log handler that inject the good Log implementation

Mbassador is a fast and flexible event bus system following the publish subscribe pattern. It is designed for ease of use and aims to be feature rich and extensible while preserving resource efficiency and performance. It provides non-blocking iterators and minimal write contention with low memory footprint. Some features: declarative handler definition via annotations, sync and/or async event delivery, weak or strong references, configurable event filters,

Nuun Kernel is a software kernel for framework creation. It brings a powerful plugin design plus a JSR 330 compliant injection mechanism backed by Guice. Plugin benefits from kernel capabilities by sendings request to it : - kernel params request : - Classpath scans request :on class by name, annotation, meta annotation or more generally Predicate - Binding Request : Nuun Kernel provides an SPI in order to bring IOC from other vendors. Nuun Kernel come with 2 plugins: - Configuration Plugin : a plugin that inject the good property based on @Property annotation. - Log plugin : a Log handler that inject the good Log implementation

Nuun Kernel is a software kernel for framework creation. It brings a powerful plugin design plus a JSR 330 compliant injection mechanism backed by Guice. Plugin benefits from kernel capabilities by sendings request to it : - kernel params request : - Classpath scans request :on class by name, annotation, meta annotation or more generally Predicate - Binding Request : Nuun Kernel provides an SPI in order to bring IOC from other vendors. Nuun Kernel come with 2 plugins: - Configuration Plugin : a plugin that inject the good property based on @Property annotation. - Log plugin : a Log handler that inject the good Log implementation

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.

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.

Axis2 is an effort to re-design and totally re-implement both Axis/Java and (eventually) Axis/C++ on a new architecture. Evolving from the now standard "handler chain" model which Axis1 pioneered, Axis2 is developing a more flexible pipeline architecture which can yet be managed and packaged in a more organized manner. This new design acknowledges the maturing of the Web services space in terms of new protocols such as WS-ReliableMessaging, WS-Security and WS-Addressing that are built on top of the base SOAP system. At the time Axis1 was designed, while it was fully expected that other protocols such as WS-ReliableMessaging would be built on top of it, there was not a proper extension architecture defined to enable clean composition of such layers. Thus, one of the key motivations for Axis2 is to provide a clean and simple environment for like Apache Sandesha and Apache WSS4J to layer on top of the base SOAP system. Another driving force for Axis2 as well as the move away from RPC oriented Web services towards more document-oriented, message style asynchronous service interactions. The Axis2 project is centered on a new representation for SOAP messages called AXIOM (AXIs Object Model). AXIOM consists of two parts: a complete XML Infoset representation and a SOAP Infoset representation on top of that. The XML Infoset representation provides a JDOM-like simple API but is built on a deferred model via a StAX-based (Streaming API for XML) pull parsing API. A key feature of AXIOM is that it allows one to stop building the XML tree and just access the pull stream directly; thus enabling both maximum flexibility and maximum performance. This approach allows us to support multiple levels of abstraction for consuming and offering Web services: using plain AXIOM, using generated code and statically data-bound data types and so on. At the time of Axis1's design, RPC-style, synchronous, request-response interactions were the order of the day for Web services. Today service interactions are much more message -oriented and exploit many different message exchange patterns. The Axis2 engine architecture is careful to not build in any assumptions of request-response patterns to ensure that it can be used easily to support arbitrary message exchange patterns.