January 2, 2026
When syntax meets hair math
Rope science, part 11 – practical syntax highlighting (2017)
Blazing-fast code coloring post derailed by math nerds
TLDR: A 2017 post shows a lean, fast way to highlight code by updating only what changed, keeping editors responsive. The top comment detoured into abstract “braid group” math, sparking a playful split between practical speed fans and theory lovers—and proving dev threads never resist a tangent.
A 2017 deep dive promises what every coder craves: code that lights up fast and sips battery, thanks to a clever “only update what changed” trick instead of reprocessing everything. Think: smoother scrolling, instant highlights, and less memory bloat. The post breaks it down simply—keep a tiny running state per line and update it incrementally—while name-dropping fancy terms like automata (read: a tidy checklist brain) without drowning readers in jargon. Practical, tidy, and very “ship it.”
And then the comments happened. The loudest energy? One user yanked the convo into brain-bending territory, asking about a link to braid groups—yes, literal knot math—in a thread about coloring code. Cue split vibes: the pragmatists cheering “this is how editors stay snappy,” the armchair theorists spiraling into abstract math, and the joke crowd riffing that we’re doing “hair math for text makeup.” It’s classic dev internet: a how-to on speed becomes a vibes war over staying practical versus summoning the math wizard. Even the link shared reads like a secret door to geometry land, and you can practically hear the coffee mugs clacking. Verdict: the algorithm wins, but the comments turned it into a rom-com between engineers and mathematicians, with syntax highlighting stuck in the middle.
Key Points
- •Proposes an incremental algorithm for syntax highlighting with strong performance in latency, memory, and power.
- •Defines a common function signature: syntax(previous_state, line) -> (next_state, spans).
- •Models state as a pushdown automaton; extension to LR parsers is possible with one-token lookahead.
- •Outlines a simple batch algorithm suitable for initial loads and serving as a correctness spec.
- •Shows that memoization enables random-access highlighting, reducing complexity from O(n^2) to O(n) with per-line state caching.