
Official website (https://ikvm.org/)
Also known as IKVM.NET
IKVM (formerly IKVM.NET) is an implementation of Java for Common Language Infrastructure implementations such as Mono and the Microsoft .NET Framework. IKVM is free software, distributed under the zlib permissive free software license.

Link to the official site · 1,202 chars · not written by Vinony
See HOWTO for the build instructions. The quick start is Install NAnt ( I found that the problem was Windows security related in that the downloaded NAnt zip file needed additional security related configuration to be performed: before extracting, one must right click on the zip file, select Properties and under the General tab, click the button labelled Unblock, the click OK on the Properties window. Now, extract the file to your desired location. Must be set to use JDK 7 (not 8 or later). Download ICSharpCode.SharpZipLib.dll ( and copy to the bin folder. Download openjdk-7u6-b24 ( and unpack in the peer folder to ikvm. In the root folder run nant. Produces a debug build with all. pdb files in the bin folder. To produce the strongly named assemblies Package NuGet build a signed version of the project from the nuget directory run these commands nant IKVM.nuspec nant nupkg To publish set your nuget Api key: then use nuget push to push nug nuget gallery:
Excerpt from the source-code README · 1,778 chars · not written by Vinony
~2 min read
IKVM (formerly IKVM.NET) is an implementation of Java for Common Language Infrastructure implementations such as Mono and the Microsoft .NET Framework. IKVM is free software, distributed under the zlib permissive free software license.
Work started on IKVM early in 2000 to assist migration of a Java-based reporting package from Sumatra to Microsoft .NET. The original developer, Jeroen Frijters, discontinued work on IKVM in 2015. In 2018, Windward Studios forked IKVM.NET to continue development on the open-sourced IKVM. In 2022 Jerome Haltom and others picked up the work on a new GitHub organization and finished .NET Core support.
via Wikidata · CC0
Discovered by embedding cosine similarity (sentence-transformers MiniLM, 384-dim).