Heap Sort: When to Use It

Start with the idea

A problem is a good match for Heap Sort when it asks for bounded-memory worst-case sorting. Here the concrete task is: Return the ascending ordering produced by an in-place max heap. The visible input [4,10,3,5,1] is an example, not a definition of the whole problem. Ask what operations the solution must support and what the input guarantees. Before sorting everything, ask whether a single statistic is enough and whether stable order among equal keys matters. The right choice follows from those guarantees, not from a familiar noun in the prompt.

The decisive invariant is: Build a max heap and repeatedly move the maximum into its final suffix position. Try to say why it applies to the task without quoting the implementation. Which fact becomes known after one update, and which possible answers remain? Sorting establishes global order; selection asks only for a rank or partition. Explain which comparisons make progress toward that goal. If that claim cannot be maintained on a legal input, the pattern is wrong or one of its preconditions is missing. A counterexample is more useful than a vague warning: change one property of the sample, trace the first two steps, and identify the exact claim that fails.

Compare costs before committing. The advertised bound is O(n log n) time · O(1) space; identify the operation responsible for it and the extra memory it needs.