Gas Station Reset: When to Use It

Start with the idea

A problem is a good match for Gas Station Reset when it asks for circular feasibility with cumulative gain. Here the concrete task is: Return a valid starting station, or -1. The visible input gas=[1,2,3,4,5] cost=[3,4,5,1,2] is an example, not a definition of the whole problem. Ask what operations the solution must support and what the input guarantees. When the method sorts intervals or events, use the coordinate and tie break required by its proof. Other greedy walks keep an invariant without sorting. The right choice follows from those guarantees, not from a familiar noun in the prompt.

The decisive invariant is: When running fuel becomes negative, no station in that failed segment can be a valid start. 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 greedy step commits to a local choice. Give the exchange or dominance reason that an optimal solution can still include that choice. 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) space; identify the operation responsible for it and the extra memory it needs.