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Luzzu is a Quality Assessment Framework for Linked Open Datasets. It is a generic framework based on the Dataset Quality Ontology (daQ), allowing users to define their own quality metrics. Luzzu is an integrated platform that: - assesses Linked Data quality using a library of generic and user-provided domain specific quality metrics in a scalable manner; - provides queryable quality metadata on the assessed datasets; - assembles detailed quality reports on assessed datasets. Furthermore, the infrastructure: - scales for the assessment of big datasets; - can be easily extended by the users by creating their custom and domain-specific pluggable metrics, either by employing a novel declarative quality metric specification language or conventional imperative plugins; - employs a comprehensive ontology framework for representing and exchanging all quality related information in the assessment workflow; - implements quality-driven dataset ranking algorithms facilitating use-case driven discovery and retrieval.

Includes 2 main parts: - Path finding through 2D polygons using the A star algorithm and navigation-mesh generation Field of vision / shadows / line of sight / lighting. The basic polygon and point classes are the KPolygon and KPoint. KPolygon contains a list of KPoints for vertices as well as a center (centroid), area, and radius (circular bound or distance from center to furthest point). KPolygon was born out of the need for a more game-oriented and flexible polygon class than the Path2D class in the standard Java library. KPolygon implements java.awt.geom.Shape so it can be easily drawn and filled by Java2D's Graphics2D object. - This API provides path-finding and field-of-vision. For other complex geometric operations such as buffering (fattening and shrinking) and constructive area geometry (intersections and unions) it is recommended to use the excellent Java Topology Suite (JTS). The standard Java2D library also provides the Area class which can be used for some constructive area geometry operations. Note that there is a utility class PolygonConverter that can quickly convert KPolygons to JTS polygons and vice versa.

Chips-n-Salsa is a Java library of customizable, hybridizable, iterative, parallel, stochastic, and self-adaptive local search algorithms. The library includes implementations of several stochastic local search algorithms, including simulated annealing, hill climbers, as well as constructive search algorithms such as stochastic sampling. Chips-n-Salsa now also includes genetic algorithms as well as evolutionary algorithms more generally. The library very extensively supports simulated annealing. It includes several classes for representing solutions to a variety of optimization problems. For example, the library includes a BitVector class that implements vectors of bits, as well as classes for representing solutions to problems where we are searching for an optimal vector of integers or reals. For each of the built-in representations, the library provides the most common mutation operators for generating random neighbors of candidate solutions, as well as common crossover operators for use with evolutionary algorithms. Additionally, the library provides extensive support for permutation optimization problems, including implementations of many different mutation operators for permutations, and utilizing the efficiently implemented Permutation class of the JavaPermutationTools (JPT) library. Chips-n-Salsa is customizable, making extensive use of Java's generic types, enabling using the library to optimize other types of representations beyond what is provided in the library. It is hybridizable, providing support for integrating multiple forms of local search (e.g., using a hill climber on a solution generated by simulated annealing), creating hybrid mutation operators (e.g., local search using multiple mutation operators), as well as support for running more than one type of search for the same problem concurrently using multiple threads as a form of algorithm portfolio. Chips-n-Salsa is iterative, with support for multistart metaheuristics, including implementations of several restart schedules for varying the run lengths across the restarts. It also supports parallel execution of multiple instances of the same, or different, stochastic local search algorithms for an instance of a problem to accelerate the search process. The library supports self-adaptive search in a variety of ways, such as including implementations of adaptive annealing schedules for simulated annealing, such as the Modified Lam schedule, implementations of the simpler annealing schedules but which self-tune the initial temperature and other parameters, and restart schedules that adapt to run length.

HockeySDK-Android implements support for using HockeyApp in your Android application. The following features are currently supported: Collect crash reports:If your app crashes, a crash log is written to the device's storage. If the user starts the app again, they will be asked asked to submit the crash report to HockeyApp. This works for both beta and live apps, i.e. those submitted to Google Play or other app stores. Crash logs contain viable information for you to help resolve the issue. Furthermore, you as a developer can add additional information to the report as well. Update Alpha/Beta apps: The app will check with HockeyApp if a new version for your alpha/beta build is available. If yes, it will show a dialog to users and let them see the release notes, the version history and start the installation process right away. You can even force the installation of certain updates. User Metrics: Understand user behavior to improve your app. Track usage through daily and monthly active users. Monitor crash impacted users. Measure customer engagement through session count. Add custom tracking calls to learn which features your users are actually using. This feature requires a minimum API level of 14 (Android 4.x Ice Cream Sandwich). Feedback: Besides crash reports, collecting feedback from your users from within your app is a great option to help with improving your app. You act on and answer feedback directly from the HockeyApp backend. Authenticate: Identify and authenticate users against your registered testers with the HockeyApp backend.

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 --debug run with debug logging ``` ### 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_2.11-2.2.4.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. For example: POST http://localhost:29999/create?state=NoUsers '{ "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 } ### /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] }'