Search Results for "org.json-1.6-20240205.jar(js=n-java)" - Page 3
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Showing 55 open source projects for "org.json-1.6-20240205.jar(js=n-java)"
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Junie, the AI coding agent by JetBrainsJunie is an AI-powered coding agent developed by JetBrains designed to enhance developer productivity by integrating directly into popular IDEs such as IntelliJ IDEA, PyCharm, and Android Studio. It supports developers by assisting with code completion, testing, and inspections, ensuring code quality and reducing debugging time.
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Haystack is a modern, engaging, and intuitive intranet platform that employees actually use.With customizable iOS and Android mobile apps, Slack and Microsoft Teams integrations, and an intuitive design employees love, Haystack brings an outstanding digital employee experience to your entire workforce, no matter where their work takes them.
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A common problem with testing tools such as NUnit and JUnit is the need to have reliable, consistent data to test against. This tool provides a way to load and unload test data into a database for unit test purposes (as well as any other data loading nee
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Project Identity aims to develop an Open source Biometric Solution i.e. complete set of tools and libraries for Biometric identifiction systems. This project has intial code done by students as their summer project at Echo IT Labs Pvt. Ltd.
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A revolutionary software development framework based on eXegeSys Customizer Technology. It allows developers to build applications that can be customized by the end user without changing the source code, interrupting support, or limiting future upgrades.
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Peet is a back-end .NET compiler for the SXM software transactional memory (STM) package (available from Microsoft Research). It makes concurrent programming with an STM library easier and more efficient.
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The AI coach for teams, built on validated assessments.Give managers and teams proactive, contextual coaching to lead effectively, communicate clearly, and navigate real work situations as they happen.
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A .Net Library that lets you make full use of multi-core and multiprocessor computers. It is very efficient, and easily integrated into existing applications. It is modeled after the Parallel FX usage model, and is faster than the PFX too.
