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Programming Heuristic "Push Ifs Up and Fors Down" Improves Code Clarity and Performance

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Key points

  • "Push ifs up" moves conditional logic to the caller.
  • "Push fors down" defers loops for batch processing.
  • Centralizes branching and enables branch-free hot loops.
  • Improves clarity and performance in code.

Origin and Principle

The "push ifs up and fors down" heuristic, recommended by TigerBeetle's Tiger Style document, advocates for centralizing control flow. It suggests that all switch/if statements should reside in a "parent" function, while non-branching logic moves to helper functions. This means conditional logic (ifs) should be handled higher up in the call stack, and iterative loops (fors) should be pushed down towards batch processing.

Applying "Push Ifs Up"

Pushing conditionals up involves moving branching logic to the caller. For example, instead of a function handling an optional input internally, the caller processes the `None` case, and the function receives a plain, guaranteed input. This narrows the function's input state space, making its preconditions explicit and acting as a form of filtering.

Applying "Push Fors Down"

Pushing loops down means deferring iteration until after data has been filtered or reduced. Rather than calling a function in a loop for each item, a batch version of the function is provided, allowing the loop to run internally without branches. This makes the "hot loop" a candidate for vectorization, potentially improving performance.

Combined Effect

When combined, these two moves allow for efficient processing. For instance, a collection of optional values can be filtered by the caller to remove `None`s and unwrapped into a vector. This vector is then passed to a batch processing function, which never encounters the `None` case, leading to clearer and potentially faster execution.

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Reporting from

The programming heuristic "push ifs up and fors down" suggests centralizing conditional logic (if statements) earlier and deferring iterative loops (for operations) later in code. This approach aims to improve code clarity by consolidating branching and enhance performance through batch processing and branch-free loops.