Disclaimer: This article is a collaboration between human insight and AI's capabilities. While aiming for perfection, some amazing output was lost. Nonetheless, what remains reflects the synergy of man and machine.
Introduction:
Programming, a dance of articulating intricate ideas, deserves a paradigm resonating with simplicity and clarity. This conceptual approach exhibits the same philosophy, aiming to present a framework both intuitive for human developers and conducive for AI. Central to this vision is the emphasis on minimalistic rules, inherently reducing complexities and paving the way for atomic, low-risk refactoring.
Flat Objects & Atomic Properties:
Objects in this design are inherently flat. Every property is atomic, think single string, number, or boolean. Abandoning nested hierarchies, naming prefixes become instrumental for logical property groupings. With alphabetical sorting of prefixed properties, a clear semblance of nesting without the complexity is possible.
Flat Folder Structures & Atomic Functions:
The folder structure in this framework has a strict constraint, no nested folders. Grouping functions into folders mirrors the root function, which acts as a tree of functions. As you delve deeper into subtrees of functions, they're partitioned into separate folders. The act of discerning which subtrees warrant their own folder stems largely from their significance in the broader schema.
Each top-level folder symbolizes a group of functions, each folder and file, leveraging prefixes, communicate any relationships among functions. Inside these folders, every file represents a function — but critically, there's a strict constraint: one function per file. This approach helps developers gauge when to split or consolidate folders, striking a balance between folder quantity and file quantity.
Atomic Operations for Streamlined Refactors:
Bisect Function: Segregate one function into two distinct entities.
Join Function: Combine two separate functions into one integrated unit.
Variable Introduction & Propagation: Within the functional framework, values are immutable. Sharing a value across functions places it in the call stack determined by the nearest common ancestor. Sharing with more functions pushes its initialization further up the stack, while removing it from some brings it closer.
Structured Rename and Refactor:
As function-files proliferate within a folder, the need to either split or consolidate folder contents emerges, hinting at the optimal organization.
Adaptive Value Propagation by Design:
At the heart of functional programming are principles that discourage mutation, this concept ensures that values referenced across functions find a logical and adaptive spot in the call stack.
Conclusion:
Simplicity, more than a virtue, is the foundation for clear development and optimal AI processing. This minimalistic vision paints the future of programming — organized, transparent, and anchored in the idea that simplistic rules foster atomic, low-risk refactoring. For AI and human developers alike, this perspective promises a transformative programming landscape.
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