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The goal of quality-check is to provide a small Java library for basic runtime code quality checks. It provides similar features to org.springframework.util.Assert or com.google.common.base.Preconditions without the need to include big libraries or frameworks such as Spring or Guava. The package quality-check tries to replace these libraries and provide all the basic code quality checks you need. The checks provided here are typically used to validate method parameters and detect errors during runtime. To detect errors before runtime we use JSR-305 Annotations. With these annotations you are able to detect possible bugs earlier. For more informations look at FindBugs™ JSR-305 support.

The goal of quality-check is to provide a small Java library for basic runtime code quality checks. It provides similar features to org.springframework.util.Assert or com.google.common.base.Preconditions without the need to include big libraries or frameworks such as Spring or Guava. The package quality-check tries to replace these libraries and provide all the basic code quality checks you need. The checks provided here are typically used to validate method parameters and detect errors during runtime. To detect errors before runtime we use JSR-305 Annotations. With these annotations you are able to detect possible bugs earlier. For more informations look at FindBugs™ JSR-305 support.

This module contains a classpath scanner, and bytecode reader. It is useful in any java runtime environment, and allows java code to parse bytecode into a meta structure of classes, annotations, methods and fields. This meta structure is used throughout xapi to allow us to extend java structures in a cross-platform compliant way (exposing services and service objects so you can hack support for whatever runtime you need). It is especially useful for fast runtime injection, and as an extensible structure during codegen (which exposes mutable interfaces for our meta structure)

Idaithalam is a low code Test automation Framework, developed using Java and Cucumber. It leverages Behavior Driven Development (BDD). Tester can create test cases/scripts in simple Excel with API Spec. Excel is a simplified way to create Json based test scripts in Idaithalam. Test cases can be created quickly and tested in minutes. As a tester, you need to create Excel and pass it to Idaithalam Framework. First, generate the Json based test scripts(Virtualan Collection) from Excel. During test execution, this test script collection can be directly utilized. Then it generates Feature files from the Virtualan Collection and its executed. Lastly, It generates test report in BDD/Cucumber style. This provide complete testing support for REST APIs, GraphQL, RDBMS DB and Kafka Event messages #idaithalam #apitesting #testautomation #restapitesting #insprintautomation #rdbmstesting #graphqltesting #kafkamessagetesting #eventvalidation #messagevalidation #cucumber #bdd Virtualan Collection is a JSON based TestScripts generated from Excel API testing can be automated using Excel, POSTMAN collection and VIRTUALAN - Utilized for API testing. - Utilized Contract testing. - Utilized Production Checkout. - Agile Testing - Progressive Regression can be done for each sprint. Reduce lot of manual effects.

A NSGA-II implementation using Java. This implementation of NSGA-II algorithm is in pure reference to the original published paper. This is not an effort to convert the originally implemented C code in Java. The original C code by the authors has not be referred to while writing this implementation. This is a fully customizable implementation of the NSGA-II algorithm, made as generic as possible. This documentation assumes you have basic understanding of the NSGA-II algorithm. Apart from the core concepts of the algorithm, everything else in this package can be implemented as per the user's choice and plugged into the algorithm dynamically. Since NSGA-II is more like a set of protocols to follow as an algorithm rather than a concrete implementation of every aspect, this package has been re-written from scratch keeping complete customizability in mind. Apart from the core concepts of the algorithm, everything is considered to be a plugin external to the algorithm that can be implemented by the user and dynamically plugged into the algorithm during runtime as needed. This opens up the possibility of the package to be used simply as a PoC or be converted into something much more complex according to the users needs.

JCQL is a tool allowing to generate boilerplate java code from existing cassandra schema. It is intended to be used with Cassandra 2.1+ due to support of UDTs (User Defined Types)/Tuples/Collections. Cassandra's UDTs/Tuples/Collections and an ability to introspect schema through java driver make it possible to automatically generate POJOs and corresponding mappers between database and java models. Properly generated java code saves development efforts and is less error-prone compared to hand coding. Accompanied with proper CI and deployment it can also guarantee consistency between database and java models at any point of application lifecycle from development to production rollout. JCQL does not rely on java reflection or annotations which means all discrepancies between actual cassandra schema and what client code expects it to be will be identified during compilation not at runtime in the middle of the night right after production release. No need to worry about Cassandra client code performance implications due to use of reflection.

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.

The Video SDKs are app development kits provided to enrich apps with video collaboration features to connect customers and communities. Use these SDKs to build apps with highly customized user interfaces along with access to raw video and audio data. Video SDKs are designed to be: * Easy to use: Import libraries, call required functions, and all video conferencing will be handled for you. * Lightweight: Video SDKs are streamlined toolkits with an enormous reduction in size compared to Meeting SDKs with all the power of Zoom's video and audio solutions. * Highly customizable: Raw video and audio data is available to you, allowing your chosen renderer to customize the video experience. Video sessions created by the Video SDKs are launched instantly, bringing a delightful video communication experience to your users with high-quality video and audio. Direct access to raw video and audio data allows improved interaction between users and the app video stream. Imagine a gaming video streaming app with direct interaction between the player and viewers based on in-game events or prompts from the community. Or, imagine an AR streaming platform with direct viewer access to the on-screen video. As with our Meeting SDKs, Video SDKs allow screen-sharing from devices, in-session chat messages, and high-quality video and audio streams similar to Zoom's core capabilities. The Video SDKs enable the following functionality in your app: * Launch a video communication session instantly * Share screen directly from your device * Send instant chat messages during the session * Capture and review raw data locally * Test different rendering schema and enjoy high-quality video and audio streams * Broadcast the video session to third-party live streaming providers To know more, see: https://developers.zoom.us/docs/video-sdk/

The Video SDKs are app development kits provided to enrich apps with video collaboration features to connect customers and communities. Use these SDKs to build apps with highly customized user interfaces along with access to raw video and audio data. Video SDKs are designed to be: * Easy to use: Import libraries, call required functions, and all video conferencing will be handled for you. * Lightweight: Video SDKs are streamlined toolkits with an enormous reduction in size compared to Meeting SDKs with all the power of Zoom's video and audio solutions. * Highly customizable: Raw video and audio data is available to you, allowing your chosen renderer to customize the video experience. Video sessions created by the Video SDKs are launched instantly, bringing a delightful video communication experience to your users with high-quality video and audio. Direct access to raw video and audio data allows improved interaction between users and the app video stream. Imagine a gaming video streaming app with direct interaction between the player and viewers based on in-game events or prompts from the community. Or, imagine an AR streaming platform with direct viewer access to the on-screen video. As with our Meeting SDKs, Video SDKs allow screen-sharing from devices, in-session chat messages, and high-quality video and audio streams similar to Zoom's core capabilities. The Video SDKs enable the following functionality in your app: * Launch a video communication session instantly * Share screen directly from your device * Send instant chat messages during the session * Capture and review raw data locally * Test different rendering schema and enjoy high-quality video and audio streams * Broadcast the video session to third-party live streaming providers To know more, see: https://developers.zoom.us/docs/video-sdk/