Hash Maps & Sets · 12 min · free with an account

Group by Canonical Key: Mental Model

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Transform each item to a stable key and collect items sharing that key.

Core idea

Preserve the invariant first; the implementation is a consequence of it.

Start with the idea

Begin with the concrete question: Group words by sorted letters and return the size of the largest group. For the visible input [eat,tea,tan,ate,nat], the stated result is 3. Before reading code, name the smallest piece of information that must survive from one step to the next. A key-derived representation lets later work reuse an earlier fact. It may be a set, a map from keys to state, compressed ranks, or a rolling fingerprint; name which one this pattern uses. That is the mental model for Group by Canonical Key; it gives you a reason for each update instead of a line of code to memorise.

The core mechanism is this: Transform each item to a stable key and collect items sharing that key. Treat it as a claim to test after every operation. Write down the state before the first operation, update it once, and ask which part of the claim is still true. If an item is skipped, inserted, or removed, explain why that action cannot destroy an answer that should be retained. A useful trace has columns for the current input position, the state before the step, the action, and the state afterward. Use the visible sample until the expected result becomes inevitable rather than merely plausible.

Now inspect the Rust sketch, not just its final expression. The supplied Rust sketch is a starting point.

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