The real meat of the story is in the referenced blog post: https://blog.codingconfessions.com/p/how-unix-spell-ran-in-64kb-ram
TL;DR
If you’re short on time, here’s the key engineering story:
McIlroy’s first innovation was a clever linguistics-based stemming algorithm that reduced the dictionary to just 25,000 words while improving accuracy.
For fast lookups, he initially used a Bloom filter—perhaps one of its first production uses. Interestingly, Dennis Ritchie provided the implementation. They tuned it to have such a low false positive rate that they could skip actual dictionary lookups.
When the dictionary grew to 30,000 words, the Bloom filter approach became impractical, leading to innovative hash compression techniques.
They computed that 27-bit hash codes would keep collision probability acceptably low, but needed compression.
McIlroy’s solution was to store differences between sorted hash codes, after discovering these differences followed a geometric distribution.
Using Golomb’s code, a compression scheme designed for geometric distributions, he achieved 13.60 bits per word—remarkably close to the theoretical minimum of 13.57 bits.
Finally, he partitioned the compressed data to speed up lookups, trading a small memory increase (final size ~14 bits per word) for significantly faster performance.
Thanks, and sorry about that! I removed the colon from near my URL now, just in case.