Variable-Size Window: When to Use It

Start with the idea

A problem is a good match for Variable-Size Window when it asks for minimum or maximum contiguous ranges under a monotone constraint. Here the concrete task is: For positive values, return the minimum length with sum at least 7. The visible input [2,3,1,2,4,3] is an example, not a definition of the whole problem. Ask what operations the solution must support and what the input guarantees. Choose this family when a valid window can be repaired by moving one boundary; non-monotone constraints may need a different method. The right choice follows from those guarantees, not from a familiar noun in the prompt.

The decisive invariant is: Expand until a constraint fails, then shrink until it is valid again. 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? A window is a contiguous interval with a maintained summary. Describe what entering the right edge adds and what leaving the left edge removes. 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) time · O(1) or state space; identify the operation responsible for it and the extra memory it needs.