The complete JIRA release notes can be found here.
Human task management is very important in the context of processes. While we allow users to plug in any task component they prefer, we have developed a human task management component that supports the entire life cycle of human tasks based on the WS-HumanTask specification, which is discussed in the following two blows:
Drools and WS-HumanTask
Creating a DSL for WS-HumanTask and when not to use a Rule Engine
Sample Eclipse views allow users to manipulate their tasks. The code can be found here.
The Drools Flow language itself has also been extended with new powerful functionality, including:
As a result, new node types and properties have been added to the Drools Flow editor in Eclipse. You can also find examples of these new features in the integration tests (e.g. ProcessExceptionHandlerTest, ProcessTimerTest, etc.).
Finally, our pluggable work item approach allows you to plug in domain-specific work in your process in a declarative manner. We plan to build a library of common work items and already provide an implementation for sending emails, finding files, archiving, executing system commands, logging and human tasks.
Drools Expert and Fusion
Drools now supports "fireUntilHalt()" feature, that starts the engine in a reactive mode, where rules will be continually fired, until a halt() call is made. This is specially useful for CEP scenarios that require what is commonly known as "active queries".
Rule Base partitioning and multi-thread propagation
Drools ReteOO algorithm now supports an option to start the rule base in a multi-thread mode, where Drools ReteOO network is split into multiple partitions and rules are then evaluated concurrently by multiple threads. This is also a requirement for CEP where there usually are several independent rules running concurrently, with near realtime performance/throughput requirements and the evaluation of one can not interfere with the evaluation of others. This is a big topic and has several implications that I will discuss in a follow up blog post and the upcoming documentation.
XSD Model Support
Drools now supports XSD models, you can look at the unit test here to see how it works. Remember though the XSD model is generated as pojos local to the Drools classloader. A helper class is there to assist in the creation of the model in the packagebuilder. Once the data model is generated you'll typically use the JAXB dataloader to insert data.
Drools now supports two data loaders, Smooks and JAXB. Smooks is an open source data transformation tool for ETL and JAXB a standard sun data mapping tool. Unit tests showing Smooks can be found here and JAXB here.