Mihaela Mihaljevic 0ce59c826b perf(parsing): allocation-free Reader.matches(), first measured pass

matches() ran on every scan decision and materialized an Array of the
literal per call, the hottest comparison in the parse profile. It now
walks the literal directly. Parse time on the 4.2 MB benchmark corpus
drops 16 percent (0.49 s to 0.41 s, libxml2 ratio 30x to 26x); profile
findings and the optimization log recorded in docs/benchmarks.md.

2026-06-10 18:21:08 +02:00

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Benchmarks: PureXML vs libxml2 (#139)

bash scripts/benchmark.sh [items] [iterations] generates a deterministic corpus (never vendored), builds PureXML in release and the C driver against the macOS SDK's libxml2, runs both over the same bytes with internal timing (best-of-N, IO excluded), and prints the comparison. Both drivers also cross-check the same XPath count, so every benchmark run doubles as a cross-implementation correctness check.

Baseline (first measurement)

20000 items, ~4.2 MB, best of 5, Apple Silicon (Studio), release builds:

operation	PureXML	libxml2	ratio
parse	0.49 s	0.016 s	~30x
serialize	0.059 s	0.012 s	~5x
xpath	0.42 s	0.012 s	~36x

These are the honest starting numbers the #139 optimization passes burn down; the table updates as passes land, never silently.

Optimization log

pass	change	parse	xpath	serialize
baseline	-	0.494 s (30x)	0.413 s (37x)	0.061 s (5.5x)
1	allocation-free Reader.matches()	0.414 s (26x)	unchanged	unchanged

Profile findings (first sample, parse path)

Top of stack, release build: String.Iterator.next (the per-character pull closure chain), _stringCompareWithSmolCheck (Character equality in matches/peek), String._uncheckedFromUTF8 and _allASCII (small-string materialization), bridgeObjectRelease/swift_release (ARC on Character buffers), UnicodeScalarView.distance. The Reader's architecture: one closure call per scalar, [Character] lookahead, Character-typed classification. The structural fix is a byte-level (UTF-8) scanner with scalar classification tables; that is its own #139 pass, designed, not patched.

Known structure of the gap

Parse and XPath dominate; serialize is closest.
The scanner-vs-tree split needs the SAX stage, blocked on #142 (the public streaming surface is internal today).
Suspects to profile, in order: Character/grapheme-based scanning versus byte scanning, per-scalar reader buffering (#135), ARC traffic in tree construction, XPath node-set materialization on every axis step.

Rules

Optimize only what these numbers indict, one suspect per pass, with the before/after recorded here.
The corpus generator changes only with a note here, since ratios are only comparable over identical corpora.

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