Showing 4 open source projects for "java projects using netbeans"

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    Multi-Entity Cloud Accounting Software for Growing Businesses

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  • Junie, the AI coding agent by JetBrains Icon
    Junie, the AI coding agent by JetBrains

    Your smart coding agent

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  • 1
    JAMon API

    JAMon API

    Monitor Java applications - SQL, HTTP, Methods, Exceptions and more.

    JAMon API is a free, simple, high performance, thread safe, Java API that allows developers to easily monitor the performance and scalability of production applications. JAMon tracks hits, execution times (total, avg, min, max, std dev), and more. * JAMon Users Manual: For more on the JAMon, including installing, configuring, and using it, see http://jamonapi.sourceforge.net/. * Support: If you have any questions about usage please post a question on the forum at http://sourceforge.net/projects/jamonapi/forums/forum/334830
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    Downloads: 37 This Week
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  • 2
    SqlWrapper
    Abstracts developers from SQL syntax, with methods that return Strings to pass on to JDBC, thus allowing compile-time checking for, many, otherwise run-time bugs. e.g. stmt.executeQuery(SqlWrapper.selectId(ordersTable, customerColumn, "John Smith")
    Downloads: 1 This Week
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  • 3
    S3 Mockup is an Amazon S3 emulator we develop for one of our projects. It can be easy embedded and used in your test framework or running as an independent service. Using this emulator you can easy setup development and QA environment.
    Downloads: 0 This Week
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  • 4
    The LAW workflow system is a Java application (using JBoss and PostgreSQL) intended to provide a file / user / task management system for projects that need to manage a pipeline of processes that are performed on some type of source file. The system is
    Downloads: 0 This Week
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  • Ango Hub | All-in-one data labeling platform Icon
    Ango Hub | All-in-one data labeling platform

    For AI teams and Computer Vision team in organizations of all size

    AI-Assisted features of the Ango Hub will automate your AI data workflows to improve data labeling efficiency and model RLHF, all while allowing domain experts to focus on providing high-quality data.
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