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This library is the the backend for the Fitzhì solution. Fitzhì aims to gather all technical data regarding your application portfolio into ONE single portal. Fitzhì provides also analysis and assessments at the project scope, but its main target is the portfolio. The main ambition is to provide a global, and dynamic vision of the technical risk for your IT. The dream functionality for Fitzhì should be the ONE single dashboard, one Single Point Point Of Quality, available for the CTO, or CIO, and ready to resume in one second, one view, the current situation and the historic trend.

The AppOptics Java instrumentation agent jar file. This artifact provides a convenient way to download the agent jar from public Maven repository. Please take note that this should NOT be included as a part of the project dependencies. Rather, this artifact should be integrated into the build process by using extra step such as the "copy" goal of "maven-dependency-plugin". For more information, please refer to https://docs.appoptics.com/kb/apm_tracing/java/install/#getting-the-agent-jar

Azure Video Analyzer provides a platform to build intelligent video applications that span the edge and the cloud. The platform offers the capability to capture, record, and analyze live videos along with publishing the results, video, and video analytics, to Azure services in the cloud or the edge. It is designed to be an extensible platform, enabling you to connect different video analysis edge modules such as Cognitive services containers, custom edge modules built by you with open-source machine learning models or custom models trained with your own data. You can then use them to analyze live video without worrying about the complexity of building and running a live video pipeline. Use the client library for Video Analyzer Edge to simplify interactions with the Microsoft Azure IoT SDKs (https://github.com/azure/azure-iot-sdks) and programmatically construct pipeline topologies and live pipelines.

Leveraging Tencent's 21 years of experience in network and audio/video technologies, Tencent Real-Time Communication (TRTC) offers multi-person audio/video calls and low-latency interactive live streaming solutions. With TRTC, you can quickly develop cost-effective, low-latency, and high-quality interactive audio/video services. Audio/Video Call Solution TRTC provides a client SDK that works across platforms and regions. This solution can be easily used on webpages to enable audio and video call capability for all applications. Low-Latency Interactive Live Streaming Solution TRTC leverages Tencent Cloud's high-quality node resources, industry-leading network and audio/video technologies to helps you build interactive live streaming services with minimal lags and a latency below 1 second, taking live streaming into the era of CDN 2.0.腾讯实时音视频（Tencent Real-Time Communication，TRTC）将腾讯21年来在网络与音视频技术上的深度积累，以多人音视频通话和低延时互动直播两大场景化方案，通过腾讯云服务向开发者开放，致力于帮助开发者快速搭建低成本、低延时、高品质的音视频互动解决方案。

A Java component which displays bytes in Hex- and ASCII-format. The component is designed as a standalone lib. A complete interface which provides the function of an HexEditor based on this lib exisits under the Fork of this project. \r\n This library is simply taken directly from sourceforge at https://sourceforge.net/projects/hexlib/ and made it available in maven central repository. No other changes have been made (including keeping the same license).

A scalable, concurrent, in-memory Key Value (KV) map. Oak implements a concurrent Key-Value map that can keep all keys and values off-heap. This enables working with bigger heap sizes than JVM's managed heap. OakMap implements an API similar to the industry standard Java8 ConcurrentNavigableMap API. It provides strong (atomic) semantics for read, write, and read-modify-write, as well as (non-atomic) range query (scan) operations, both forward and backward. OakMap is optimized for big keys and values, in particular, for incremental maintenance of objects (update in-place). It is faster and scales better with additional CPU cores than the popular Java ConcurrentNavigableMap ConcurrentSkipListMap

Test Drop-in Framework for Selenium WebDriver 4.1.x This repository contains these major deliverables: a) the Test Drop-in Framework, b) a WebDriver implementation offering enhanced logging capabilities, and c) the @FindByJS annotation support Provides a thin abstraction layer between the test environment and the test class plus its helpers. This makes the test code independent of the test environment, thus allowing exchange of tests between organizations or even companies. It comes with an event firing WebDriver wrapper plus corresponding interface. This allows you to implement listeners to arbitrary WebDriver activities for various purposes such as logging. Offers support of JavaScript commands to find elements in a way similar to @FindBy used on fields in Page Object classes.