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Module that defines the HttpChannel API. HttpChannels abstract complex download and upload steps into a simple and easy to use NIO Channel. NIO Channels can be wrapped into an InputStream or OutputStream and used in any way you may find possible to. Aside from that, Channels can be used natively in most next-gen libraries, meaning that you don't even need to wrap anything, just start writing or reading data to or from the channel wth a ByteBuffer. Anyone using the library should try to rely on code from this module only and, only if necessary, on configuration classes that are implementation specific. Relying on any other resource or class is considered an error and should NOT be done. One of the most interesting usages of channels for uploads and download is that you can easily copy data straight from one channel to the other, with less than 10 lines of code! Also, channels allows the implementation of a "tee" mechanism, in which data redden from a single channel can be copied to several other channels on the fly!

GlassFish build depends on properly functioning several custom lifecycle mappings and artifact handlers. Because these are necessary to resolve dependencies and to run "gf:run" goal and etc., it is critical that these extensions be made available to Maven early on during Maven execution. This definition was originally in maven-glassfish-plugin, which was integrated into Maven POM through <plugin>/<extensions>true marking, but after a series of debugging to resolve artifact resolution failure problems, it turns out that that doesn't cause Maven to load components early enough. I tried to circumbent the prolem by also registering the maven-glassfish-plugin as an extension module (via <build>/<extensions/<extension>), but that apparently confuses Maven to no end --- I get build errors like this: [INFO] Internal error in the plugin manager executing goal 'org.apache.maven.plugins:maven-jar-plugin:2.1:jar': Unable to find the mojo 'org.apache.maven.plugins:maven-jar-plugin:2.1:jar' in the plugin 'org.apache.maven.plugins:maven-jar-plugin' This is obviously one of the problematic areas of Maven, so to avoid doing hack over hack, I'm simply moving the component definitions to its own module.

GlassFish build depends on properly functioning several custom lifecycle mappings and artifact handlers. Because these are necessary to resolve dependencies and to run "gf:run" goal and etc., it is critical that these extensions be made available to Maven early on during Maven execution. This definition was originally in maven-glassfish-plugin, which was integrated into Maven POM through <plugin>/<extensions>true marking, but after a series of debugging to resolve artifact resolution failure problems, it turns out that that doesn't cause Maven to load components early enough. I tried to circumbent the prolem by also registering the maven-glassfish-plugin as an extension module (via <build>/<extensions/<extension>), but that apparently confuses Maven to no end --- I get build errors like this: [INFO] Internal error in the plugin manager executing goal 'org.apache.maven.plugins:maven-jar-plugin:2.1:jar': Unable to find the mojo 'org.apache.maven.plugins:maven-jar-plugin:2.1:jar' in the plugin 'org.apache.maven.plugins:maven-jar-plugin' This is obviously one of the problematic areas of Maven, so to avoid doing hack over hack, I'm simply moving the component definitions to its own module.

[](https://drone.io/bitbucket.org/tidalwave/tidalwave-superpom-src/latest) The super POM for all Tidalwave projects. It is not designed for being used by others, as it contains some corporate-specific configurations, but its ancestor [TheseFooolishThings SuperPOM](http://bitbucket.org/tidalwave/thesefoolishthings-superpom-src) has been designed to be reusable. Please have a look at it. This super POM adds to its ancestor: + some Tidalwave variables that refers to the issue tracker, continuous integration system, etc...; + the definitions of versions of a number of commonly used libraries and their dependency management: * [AspectJ](https://www.eclipse.org/aspectj) * [Hamcrest Matchers](http://hamcrest.org/JavaHamcrest) * [JSR 330](https://github.com/google/guice/wiki/JSR330) * [Jakarta XML Binding (JAXB)](https://eclipse-ee4j.github.io/jaxb-ri/) * [Spotbugs annotations](https://spotbugs.readthedocs.io) * [JUnit](https://junit.org/junit5) * [Logback](http://logback.qos.ch) * [Lombok](https://projectlombok.org) * [SLF4J](slf4j.org) * [Spring 5](https://spring.io/projects/spring-framework) * [TestNG](https://testng.org) + the definition for Tidalwave 3rd party repository (stuff that is not available on Maven Central); + a profile for using the [TheseFoolishThings](http://tidalwave.it/projects/thesefoolishthings) Event Bus (```it.tidalwave-spring-messagebus-v1```); + profiles for the [Mycila License plugin](https://github.com/mycila/license-maven-plugin); + configuration of the UMLGraphDoc maven plugin; + the configuration for the TheseFoolishThings TestNG listener (which provides enhanced test logging); + definitions of some custom javadoc tags; + a blacklist for some old artifacts; + some other minor customisations.

Jadex Rules is a small lightweight rule engine, which currently employs the well-known Rete algorithm for highly efficient rule matching. Jadex rules is therefore similar to other rule engines like JESS and Drools. Despite the similarities there are also important differences between these systems: * Jadex Rules is very small and intended to be used as component of other software. Even though rules can be specified in a Java dialect as well as (a small variation of) the CLIPS language its primary usage is on the API level. Jadex Rules is currently the core component of the Jadex BDI reasoning engine. * Jadex Rules cleanly separates between state and rule representation. This allows the state implementation as well as the matcher to be flexibly exchanged. Some experiments have e.g. been conducted with a Jena representation. Regarding the matcher, it is planned to support also the Treat algorithm, which has a lower memory footprint than Rete. * Jadex Rules pays close attention to rule debugging. The state as well as the rete engine can be observed at runtime. The rule debugger provides functionalities to execute a rule program stepwise and also use rule breakpoints to stop the execution at those points.

JUNG the Java Universal Network/Graph Framework--is a software library that provides a common and extensible language for the modeling, analysis, and visualization of data that can be represented as a graph or network. It is written in Java, which allows JUNG-based applications to make use of the extensive built-in capabilities of the Java API, as well as those of other existing third-party Java libraries. The JUNG architecture is designed to support a variety of representations of entities and their relations, such as directed and undirected graphs, multi-modal graphs, graphs with parallel edges, and hypergraphs. It provides a mechanism for annotating graphs, entities, and relations with metadata. This facilitates the creation of analytic tools for complex data sets that can examine the relations between entities as well as the metadata attached to each entity and relation. The current distribution of JUNG includes implementations of a number of algorithms from graph theory, data mining, and social network analysis, such as routines for clustering, decomposition, optimization, random graph generation, statistical analysis, and calculation of network distances, flows, and importance measures (centrality, PageRank, HITS, etc.). JUNG also provides a visualization framework that makes it easy to construct tools for the interactive exploration of network data. Users can use one of the layout algorithms provided, or use the framework to create their own custom layouts. In addition, filtering mechanisms are provided which allow users to focus their attention, or their algorithms, on specific portions of the graph.

JUNG the Java Universal Network/Graph Framework--is a software library that provides a common and extendible language for the modeling, analysis, and visualization of data that can be represented as a graph or network. It is written in Java, which allows JUNG-based applications to make use of the extensive built-in capabilities of the Java API, as well as those of other existing third-party Java libraries. The JUNG architecture is designed to support a variety of representations of entities and their relations, such as directed and undirected graphs, multi-modal graphs, graphs with parallel edges, and hypergraphs. It provides a mechanism for annotating graphs, entities, and relations with metadata. This facilitates the creation of analytic tools for complex data sets that can examine the relations between entities as well as the metadata attached to each entity and relation. The current distribution of JUNG includes implementations of a number of algorithms from graph theory, data mining, and social network analysis, such as routines for clustering, decomposition, optimization, random graph generation, statistical analysis, and calculation of network distances, flows, and importance measures (centrality, PageRank, HITS, etc.). JUNG also provides a visualization framework that makes it easy to construct tools for the interactive exploration of network data. Users can use one of the layout algorithms provided, or use the framework to create their own custom layouts. In addition, filtering mechanisms are provided which allow users to focus their attention, or their algorithms, on specific portions of the graph.

Jadex Rules is a small lightweight rule engine, which currently employs the well-known Rete algorithm for highly efficient rule matching. Jadex rules is therefore similar to other rule engines like JESS and Drools. Despite the similarities there are also important differences between these systems: * Jadex Rules is very small and intended to be used as component of other software. Even though rules can be specified in a Java dialect as well as (a small variation of) the CLIPS language its primary usage is on the API level. Jadex Rules is currently the core component of the Jadex BDI reasoning engine. * Jadex Rules cleanly separates between state and rule representation. This allows the state implementation as well as the matcher to be flexibly exchanged. Some experiments have e.g. been conducted with a Jena representation. Regarding the matcher, it is planned to support also the Treat algorithm, which has a lower memory footprint than Rete. * Jadex Rules pays close attention to rule debugging. The state as well as the rete engine can be observed at runtime. The rule debugger provides functionalities to execute a rule program stepwise and also use rule breakpoints to stop the execution at those points.