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Explore FunctionFusion.jl, an algorithm composition framework designed to bridge the gap between research and production environments in Julia development. Learn how this framework enables engineers to decompose complex algorithms into smaller, testable components while maintaining optimal performance through static algorithm generation. Discover techniques for creating modular, reusable functions with narrow responsibilities and no side effects, promoting better software architecture practices. Understand how FunctionFusion.jl addresses the challenge of environment differences by allowing computational block replacement, ensuring consistent behavior between development and production systems. Examine the framework's performance optimization capabilities, which leverage Julia's inference system to generate assembly code equivalent to hand-written functions. Gain insights into domain-specific language design that connects teams with diverse concerns and goals in algorithm development and deployment.
