Download JAR files tagged by differences with all dependencies

Sirix is a versioned, treebased storage system. It provides an ID-less diff-algorithm to import differences between two versions (currently XML-documents). Furthermore an ID-based diff-algorithm facilitates the comparison of versions stored within Sirix. A GUI with several visualizations for comparing these versions visually is available to aid an analyst. Versions are stored using well known versioning strategies (full, incremental, differential). The architecture is especially well suited for flash-disks because of a COW-principle. In the future we aim to provide throughout security as well as a replaced page-structure to speedup our architecture. A brackit(.org) binding will enable XQuery and the XQuery Update Facility. Temporal XPath axis and possibly diff-functions will help analysts to gain quick knowledge from the stored data.

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.

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.

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.

This is the main aggregator for all gwt submodules. All gwt-specific code resides here. Submodules should avoid inheriting from each other unless necessary. This goes for maven structure and gwt.xml structure. The super module is where our jre emulation layer and super-source live; all modules should inherit super, and a minimum of other modules. Some modules, like injection, are fulfilling an api in the core module, and should be accessed only through core service interfaces. Other modules, like reflection, are capable of being standalone inherits, but can benefit from core utilities like injection, so, two (or more) .gwt.xml modules may be provided. As XApi nears 1.0, all submodules will be routinely stitched together into an uber-jar, in order to have a single jar with a single gwt module that can provide all of the services at once. Internal projects will never use the uber jar, to help maintain modularity, but external projects that want to use more than one service will certainly prefer inheriting one artifact, instead of twelve. When distributed in uber-jar format, it will likely be necessary for either the uber jar, or just xapi-gwt-api.jar to appear before gwt-dev on your compile-time classpath. If using gwt-maven-plugin, the gwtFirstOnClasspath option may become problematic. If so, we will provide a forked gwt-plugin to make sure our compiler enhancements are included in the build process. There is also work going on to make a super-source-everything plugin, which will use maven to find source files, and generate synthetic .gwt.xml for you, as part of an effort to create a wholly unified programming environment. In addition to java-to-javascript, we intend to compile java-to-java and possibly other languages, like go; imagine implementing gwt deferred binding to eliminate cross-platform differences between server environments, or operating systems, or versions of a platform, or anywhere else a core api needs to bind to multiple implementations, depending on the runtime environment.

Introducing "PerScope" Library: Simplifying Privacy Policy Event Handling for Android Apps "PerScope" is a cutting-edge library designed to streamline the processing of privacy policy events within regions where compliance with local legislation is crucial. Specifically crafted for Android applications, this library addresses the intricate task of managing privacy policy-related events while adhering to the legal requirements of the country in which the app is deployed. In today's digital landscape, ensuring user privacy and data protection is of paramount importance. Different countries have varying legal frameworks dictating how user data should be handled, necessitating robust mechanisms to accommodate these differences seamlessly. This is where the "PerScope" library shines. The key feature that sets "PerScope" apart is its incredible simplicity. With just a single function call, developers can integrate the library into their Android applications and gain immediate access to a comprehensive suite of tools for managing privacy policy events. Whether it's presenting privacy-related notifications, tracking user consents, or adapting the app's behavior based on regional requirements, "PerScope" handles it all efficiently and effectively. Here's a glimpse of what "PerScope" brings to the table: Localized Compliance: "PerScope" empowers developers to align their apps with the privacy laws of each region. By intelligently detecting the user's location, the library ensures that the app's behavior remains compliant with the specific privacy regulations of that area. Event Handling Made Easy: Instead of grappling with complex event management code, developers can integrate the "PerScope" function, drastically reducing development time and effort. The library takes care of the intricate event handling process seamlessly. Dynamic Adaptation: With the ability to dynamically adapt the app's features based on the user's consent and the local legal requirements, "PerScope" ensures a personalized and compliant user experience. Notification Presentation: "PerScope" assists in presenting privacy-related notifications to users, making it easier to inform them about data collection practices and obtain necessary consents. Smooth Integration: The library is designed to be easily integrated into existing Android applications, minimizing disruptions to the development process. In a nutshell, "PerScope" is a developer's go-to solution for managing privacy policy events within Android apps. Its single-function approach, combined with its capacity to handle a complex and critical aspect of app development, makes it an indispensable tool for app creators aiming to provide a user-centric, privacy-respecting experience while complying with regional legislation. Stay on the right side of the law and prioritize user privacy with the power of "PerScope."

Pact server =========== The pact server is a stand-alone interactions recorder and verifier, aimed at clients that are non-JVM or non-Ruby based. The pact client for that platform will need to be implemented, but it only be responsible for generating the `JSON` interactions, running the tests and communicating with the server. The server implements a `JSON` `REST` Admin API with the following endpoints. / -> For diagnostics, currently returns a list of ports of the running mock servers. /create -> For initialising a test server and submitting the JSON interactions. It returns a port /complete -> For finalising and verifying the interactions with the server. It writes the `JSON` pact file to disk. ## Running the server ### Versions 2.2.6+ Pact server takes the following parameters: ``` Usage: pact-jvm-server [options] [port] port port to run on (defaults to 29999) --help prints this usage text -h <value> | --host <value> host to bind to (defaults to localhost) -l <value> | --mock-port-lower <value> lower bound to allocate mock ports (defaults to 20000) -u <value> | --mock-port-upper <value> upper bound to allocate mock ports (defaults to 40000) -d | --daemon run as a daemon process -v <value> | --pact-version <value> pact version to generate for (2 or 3) -k <value> | --keystore-path <value> Path to keystore -p <value> | --keystore-password <value> Keystore password -s <value> | --ssl-port <value> Ssl port the mock server should run on. lower and upper bounds are ignored --debug run with debug logging ``` ### Using trust store 3.4.0+ Trust store can be used. However, it is limited to a single port for the time being. ### Prior to version 2.2.6 Pact server takes one optional parameter, the port number to listen on. If not provided, it will listen on 29999. It requires an active console to run. ### Using a distribution archive You can download a [distribution from maven central](http://search.maven.org/remotecontent?filepath=au/com/dius/pact-jvm-server_2.11/2.2.4/). There is both a ZIP and TAR archive. Unpack it to a directory of choice and then run the script in the bin directory. ### Building a distribution bundle You can build an application bundle with gradle by running (for 2.11 version): $ ./gradlew :pact-jvm-server_2.11:installdist This will create an app bundle in `build/2.11/install/pact-jvm-server_2.11`. You can then execute it with: $ java -jar pact-jvm-server/build/2.10/install/pact-jvm-server_2.11/lib/pact-jvm-server_2.11-3.2.11.jar or with the generated bundle script file: $ pact-jvm-server/build/2.11/install/pact-jvm-server_2.11/bin/pact-jvm-server_2.11 By default will run on port `29999` but a port number can be optionally supplied. ### Running it with docker You can use a docker image to execute the mock server as a docker container. $ docker run -d -p 8080:8080 -p 20000-20010:20000-20010 uglyog/pact-jvm-server This will run the main server on port 8080, and each created mock server on ports 20000-20010. You can map the ports to any you require. ## Life cycle The following actions are expected to occur * The client calls `/create` to initialise a server with the expected `JSON` interactions and state * The admin server will start a mock server on a random port and return the port number in the response * The client will execute its interaction tests against the mock server with the supplied port * Once finished, the client will call `/complete' on the Admin API, posting the port number * The pact server will verify the interactions and write the `JSON` `pact` file to disk under `/target` * The mock server running on the supplied port will be shutdown. ## Endpoints ### /create The client will need `POST` to `/create` the generated `JSON` interactions, also providing a state as a query parameter and a path. For example: POST http://localhost:29999/create?state=NoUsers&path=/sub/ref/path '{ "provider": { "name": "Animal_Service"}, ... }' This will create a new running mock service provider on a randomly generated port. The port will be returned in the `201` response: { "port" : 34423 } But you can also reference the path from `/sub/ref/path` using the server port. The service will not strip the prefix path, but instead will use it as a differentiator. If your services do not have differences in the prefix of their path, then you will have to use the port method. ### /complete Once the client has finished running its tests against the mock server on the supplied port (in this example port `34423`) the client will need to `POST` to `/complete` the port number of the mock server that was used. For example: POST http://localhost:29999/complete '{ "port" : 34423 }' This will cause the Pact server to verify the interactions, shutdown the mock server running on that port and writing the pact `JSON` file to disk under the `target` directory. ### / The `/` endpoint is for diagnostics and to check that the pact server is running. It will return all the currently running mock servers port numbers. For example: GET http://localhost:29999/ '{ "ports": [23443,43232] }'

Pact server =========== The pact server is a stand-alone interactions recorder and verifier, aimed at clients that are non-JVM or non-Ruby based. The pact client for that platform will need to be implemented, but it only be responsible for generating the `JSON` interactions, running the tests and communicating with the server. The server implements a `JSON` `REST` Admin API with the following endpoints. / -> For diagnostics, currently returns a list of ports of the running mock servers. /create -> For initialising a test server and submitting the JSON interactions. It returns a port /complete -> For finalising and verifying the interactions with the server. It writes the `JSON` pact file to disk. ## Running the server ### Versions 2.2.6+ Pact server takes the following parameters: ``` Usage: pact-jvm-server [options] [port] port port to run on (defaults to 29999) --help prints this usage text -h <value> | --host <value> host to bind to (defaults to localhost) -l <value> | --mock-port-lower <value> lower bound to allocate mock ports (defaults to 20000) -u <value> | --mock-port-upper <value> upper bound to allocate mock ports (defaults to 40000) -d | --daemon run as a daemon process -v <value> | --pact-version <value> pact version to generate for (2 or 3) -k <value> | --keystore-path <value> Path to keystore -p <value> | --keystore-password <value> Keystore password -s <value> | --ssl-port <value> Ssl port the mock server should run on. lower and upper bounds are ignored --debug run with debug logging ``` ### Using trust store 3.4.0+ Trust store can be used. However, it is limited to a single port for the time being. ### Prior to version 2.2.6 Pact server takes one optional parameter, the port number to listen on. If not provided, it will listen on 29999. It requires an active console to run. ### Using a distribution archive You can download a [distribution from maven central](http://search.maven.org/remotecontent?filepath=au/com/dius/pact-jvm-server_2.11/2.2.4/). There is both a ZIP and TAR archive. Unpack it to a directory of choice and then run the script in the bin directory. ### Building a distribution bundle You can build an application bundle with gradle by running (for 2.11 version): $ ./gradlew :pact-jvm-server_2.11:installdist This will create an app bundle in `build/2.11/install/pact-jvm-server_2.11`. You can then execute it with: $ java -jar pact-jvm-server/build/2.10/install/pact-jvm-server_2.11/lib/pact-jvm-server_2.11-3.2.11.jar or with the generated bundle script file: $ pact-jvm-server/build/2.11/install/pact-jvm-server_2.11/bin/pact-jvm-server_2.11 By default will run on port `29999` but a port number can be optionally supplied. ### Running it with docker You can use a docker image to execute the mock server as a docker container. $ docker run -d -p 8080:8080 -p 20000-20010:20000-20010 uglyog/pact-jvm-server This will run the main server on port 8080, and each created mock server on ports 20000-20010. You can map the ports to any you require. ## Life cycle The following actions are expected to occur * The client calls `/create` to initialise a server with the expected `JSON` interactions and state * The admin server will start a mock server on a random port and return the port number in the response * The client will execute its interaction tests against the mock server with the supplied port * Once finished, the client will call `/complete' on the Admin API, posting the port number * The pact server will verify the interactions and write the `JSON` `pact` file to disk under `/target` * The mock server running on the supplied port will be shutdown. ## Endpoints ### /create The client will need `POST` to `/create` the generated `JSON` interactions, also providing a state as a query parameter and a path. For example: POST http://localhost:29999/create?state=NoUsers&path=/sub/ref/path '{ "provider": { "name": "Animal_Service"}, ... }' This will create a new running mock service provider on a randomly generated port. The port will be returned in the `201` response: { "port" : 34423 } But you can also reference the path from `/sub/ref/path` using the server port. The service will not strip the prefix path, but instead will use it as a differentiator. If your services do not have differences in the prefix of their path, then you will have to use the port method. ### /complete Once the client has finished running its tests against the mock server on the supplied port (in this example port `34423`) the client will need to `POST` to `/complete` the port number of the mock server that was used. For example: POST http://localhost:29999/complete '{ "port" : 34423 }' This will cause the Pact server to verify the interactions, shutdown the mock server running on that port and writing the pact `JSON` file to disk under the `target` directory. ### / The `/` endpoint is for diagnostics and to check that the pact server is running. It will return all the currently running mock servers port numbers. For example: GET http://localhost:29999/ '{ "ports": [23443,43232] }'

Pact server =========== The pact server is a stand-alone interactions recorder and verifier, aimed at clients that are non-JVM or non-Ruby based. The pact client for that platform will need to be implemented, but it only be responsible for generating the `JSON` interactions, running the tests and communicating with the server. The server implements a `JSON` `REST` Admin API with the following endpoints. / -> For diagnostics, currently returns a list of ports of the running mock servers. /create -> For initialising a test server and submitting the JSON interactions. It returns a port /complete -> For finalising and verifying the interactions with the server. It writes the `JSON` pact file to disk. ## Running the server ### Versions 2.2.6+ Pact server takes the following parameters: ``` Usage: pact-jvm-server [options] [port] port port to run on (defaults to 29999) --help prints this usage text -h <value> | --host <value> host to bind to (defaults to localhost) -l <value> | --mock-port-lower <value> lower bound to allocate mock ports (defaults to 20000) -u <value> | --mock-port-upper <value> upper bound to allocate mock ports (defaults to 40000) -d | --daemon run as a daemon process -v <value> | --pact-version <value> pact version to generate for (2 or 3) -k <value> | --keystore-path <value> Path to keystore -p <value> | --keystore-password <value> Keystore password -s <value> | --ssl-port <value> Ssl port the mock server should run on. lower and upper bounds are ignored --debug run with debug logging ``` ### Using trust store 3.4.0+ Trust store can be used. However, it is limited to a single port for the time being. ### Prior to version 2.2.6 Pact server takes one optional parameter, the port number to listen on. If not provided, it will listen on 29999. It requires an active console to run. ### Using a distribution archive You can download a [distribution from maven central](http://search.maven.org/remotecontent?filepath=au/com/dius/pact-jvm-server_2.11/2.2.4/). There is both a ZIP and TAR archive. Unpack it to a directory of choice and then run the script in the bin directory. ### Building a distribution bundle You can build an application bundle with gradle by running (for 2.11 version): $ ./gradlew :pact-jvm-server_2.11:installdist This will create an app bundle in `build/2.11/install/pact-jvm-server_2.11`. You can then execute it with: $ java -jar pact-jvm-server/build/2.10/install/pact-jvm-server_2.11/lib/pact-jvm-server_2.11-3.2.11.jar or with the generated bundle script file: $ pact-jvm-server/build/2.11/install/pact-jvm-server_2.11/bin/pact-jvm-server_2.11 By default will run on port `29999` but a port number can be optionally supplied. ### Running it with docker You can use a docker image to execute the mock server as a docker container. $ docker run -d -p 8080:8080 -p 20000-20010:20000-20010 uglyog/pact-jvm-server This will run the main server on port 8080, and each created mock server on ports 20000-20010. You can map the ports to any you require. ## Life cycle The following actions are expected to occur * The client calls `/create` to initialise a server with the expected `JSON` interactions and state * The admin server will start a mock server on a random port and return the port number in the response * The client will execute its interaction tests against the mock server with the supplied port * Once finished, the client will call `/complete' on the Admin API, posting the port number * The pact server will verify the interactions and write the `JSON` `pact` file to disk under `/target` * The mock server running on the supplied port will be shutdown. ## Endpoints ### /create The client will need `POST` to `/create` the generated `JSON` interactions, also providing a state as a query parameter and a path. For example: POST http://localhost:29999/create?state=NoUsers&path=/sub/ref/path '{ "provider": { "name": "Animal_Service"}, ... }' This will create a new running mock service provider on a randomly generated port. The port will be returned in the `201` response: { "port" : 34423 } But you can also reference the path from `/sub/ref/path` using the server port. The service will not strip the prefix path, but instead will use it as a differentiator. If your services do not have differences in the prefix of their path, then you will have to use the port method. ### /complete Once the client has finished running its tests against the mock server on the supplied port (in this example port `34423`) the client will need to `POST` to `/complete` the port number of the mock server that was used. For example: POST http://localhost:29999/complete '{ "port" : 34423 }' This will cause the Pact server to verify the interactions, shutdown the mock server running on that port and writing the pact `JSON` file to disk under the `target` directory. ### / The `/` endpoint is for diagnostics and to check that the pact server is running. It will return all the currently running mock servers port numbers. For example: GET http://localhost:29999/ '{ "ports": [23443,43232] }'