Home » Author Archives: Geoffrey De Smet

Author Archives: Geoffrey De Smet

Geoffrey De Smet (Red Hat) is the lead and founder of OptaPlanner. Before joining Red Hat in 2010, he was formerly employed as a Java consultant, an A.I. researcher and an enterprise application project lead. He has contributed to many open source projects (such as drools, jbpm, pressgang, spring-richclient, several maven plugins, weld, arquillian, ...). Since he started OptaPlanner in 2006, he’s been passionately addicted to planning optimization.

Drools 7 to support DMN (Decision Model and Notation)

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The Decision Model and Notation (DMN) specification is a relatively new standard by OMG (Object Management Group) that aims to do for business rules and business decisions what BPMN (it’s sibling specification) did for business processes: standardize the notation and execution semantics to enable both its use by business users, and the interchange of models between tools from different vendors. The Drools ...

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Drools 6.5.0.Final is available

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The latests and greatest Drools 6.5.0.Final release is now available for download. This is an incremental release on our previous build that focus on a few key improvements to round up the 6.x series. You can find more details, downloads and documentation here: Drools website Downloads Documentation Release Notes Read below some of the highlights of the release. You can also ...

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Security management in jBPM & Drools workbenches

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The jBPM 7 release will include an integrated security management solution to allow administrator users to manage the application’s users, groups and permissions using an intuitive and friendly user interface. Once released, users will be able to configure who can access the different resources and features available in the workbench. In that regards, a first implementation of the user & ...

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7 ways to fail your optimization project

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When you put your optimization project into production, your enterprise will decrease expenses, increase customer satisfaction, improve employee happiness and/or reduce its ecological footprint. But if the end-users reject your implementation, none of that will happen. Let’s take a look why they might do that. There are 7 common ways to fail your optimization project: Ignore the user’s plan Neglect ...

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Keycloak SSO Integration into jBPM and Drools Workbench

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Introduction Single Sign On (SSO) and related token exchange mechanisms are becoming the most common scenario for the authentication and authorization in different environments on the web, specially when moving into the cloud. This article talks about the integration of Keycloak with jBPM or Drools applications in order to use all the features provided on Keycloak. Keycloak is an integrated SSO ...

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Drools: A detailed description of internal code cleanups for fireAllRules, fireUntilHalt and Timers

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In June we blogged about a new internal state machine to manage the interaction of User, Timer and Engine threads. We’ve now done another big internal clean up of this code, to make it easier to read and easier to understand. As previous mentioned all actions (insert, update, delete etc) are now placed into a thread safe propagation queue. The ...

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Using a rective stream as a data source for Drools

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A few months ago we started redesigning the Drools lowest level executable model and making it accessible to end user with a Java 8 API. To demonstrate the flexibility of this approach I tried to integrate it with a reactive stream and in particular to use this stream as a data source for Drools. To show how this works I ...

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Integrating JPA Hibernate with OptaPlanner

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We’ve been improving the integration of OptaPlanner with the rest of JEE, so it’s easier to build end user applications that just work. Let’s take a look at the improved JPA Hibernate integration. The basics Both JPA Hibernate and OptaPlanner work on POJO’s (Plain Old Java Objects), so just add some JPA annotations on your domain objects to persist them ...

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What is the fastest Garbage Collector in Java 8?

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OpenJDK 8 has several Garbage Collector algorithms, such as Parallel GC, CMS and G1. Which one is the fastest? What will happen if the default GC changes from Parallel GC in Java 8 to G1 in Java 9 (as currently proposed)? Let’s benchmark it. Benchmark methodology Run the same code 6 times with a different VM argument (-XX:+UseSerialGC, -XX:+UseParallelGC, -XX:+UseConcMarkSweepGC, ...

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