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Vegeta is an HTTP load testing tool written in Go that can be used as a command in a command-line interface or as a library. [4] The program tests how an HTTP-based application behaves when multiple users access it at the same time [4] by generating a background load of GET requests. [5]
Google developed Protocol Buffers for internal use and provided a code generator for multiple languages under an open-source license. The design goals for Protocol Buffers emphasized simplicity and performance. In particular, it was designed to be smaller and faster than XML. [3]
Hugo is a static site generator written in Go.Steve Francia [4] originally created Hugo as an open source project in 2013. Since v0.14 in 2015, [5] Hugo has continued development under the lead of Bjørn Erik Pedersen with other contributors.
Well-formed output language code fragments Any programming language (proven for C, C++, Java, C#, PHP, COBOL) gSOAP: C / C++ WSDL specifications C / C++ code that can be used to communicate with WebServices. XML with the definitions obtained. Microsoft Visual Studio LightSwitch: C# / VB.NET Active Tier Database schema
However, parser generators for context-free grammars often support the ability for user-written code to introduce limited amounts of context-sensitivity. (For example, upon encountering a variable declaration, user-written code could save the name and type of the variable into an external data structure, so that these could be checked against ...
LangChain was launched in October 2022 as an open source project by Harrison Chase, while working at machine learning startup Robust Intelligence. The project quickly garnered popularity, [3] with improvements from hundreds of contributors on GitHub, trending discussions on Twitter, lively activity on the project's Discord server, many YouTube tutorials, and meetups in San Francisco and London.
Being able to run code at compile time allows Zig to have the functionality of macros and conditional compilation without the need for a separate preprocessor language. [15] During compile time, types become first-class citizens. This enables compile-time duck typing, and is how Zig implements generic types. [22]
This LIR performs register allocation and then generates native machine code in a process called Code Generation. The optimizations here assume that a script continues to see data similar what has been seen before. The Baseline JITs are essential to success here because they generate ICs that match observed data.