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Exercise concentrated prefixes and an 8,000-input capacity target. Check allowed and denied reads with actual sandbox enforcement. Assisted-by: Codex, GPT-6-Astra medium
Pair adjacent first hash characters to reduce prefix guards from 32 to 16, which results in some compute time savings, esp. for large profiles. On macOS 27, median profile compilation reduced from 762 to 118 ms (6.46x) for a 1,403-input build. Compiled size increased by 0.36%. Repeated trivial build probes showed a small per-operation cost, most clearly about 2-3% slower stat on Python/Nix profiles. Ten runs of hello, Git, and Python build-phase replays found no detectable total-time change. Assisted-by: Codex, GPT-6-Astra medium
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For the record, I am not entirely convinced that shaving off 0.5 to a few seconds per darwinConfiguration build justifies this (even if mild) complexity. I will let maintainers to assess. Regardless, I think we should consider including the tests for large profiles to establish some regression baseline for future changes. |
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Motivation
Bucketing performance is sensitive to the number of guards.
With the change, on macOS 27, median profile compilation reduced from 762 to 118 ms (6.46x) for a 1,403-input build. Compiled size increased by 0.36%.
Repeated trivial build probes showed a small per-operation cost, most clearly about 2-3% slower stat on Python/Nix profiles. Ten runs of hello, Git, and Python build-phase replays found no detectable total-time change.
Implementation
Pair adjacent first hash characters to reduce prefix guards from 32 to 16.
Also, added some functional tests to verify profile compilation and guard behavior for large profiles. (This piece is logically independent from the optimization but establishes the baseline as the first commit in the PR to avoid any size-sensitive regressions.)
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