Range Coverage: Minimum Intervals to Cover a Target

Concepts: pyRangeCoverage, pyGreedyCoverage, pyJumpGame

The range coverage problem: given a target range [start, end] and a list of intervals, find the minimum number of intervals needed to fully cover the target. This appears in data engineering as: 'Given a set of pipeline jobs that each cover a time range, what is the minimum number of jobs needed to ensure no data gap in the target window?' The greedy strategy is: sort by start, greedily pick the interval that extends coverage furthest. Greedy Coverage Algorithm The greedy correctness argument: at any point in the coverage sweep, we have covered up to current_end. Among all intervals that START within what we have already covered (start <= current_end), we must choose one to extend with. Choosing the one that goes farthest right is optimal — any other choice covers strictly less ground and