Sort by start, then walk through and extend the current interval if the next one overlaps, otherwise push and move on.
Start by clarifying the problem: intervals are closed, meaning they include endpoints, so overlapping occurs when one interval's start is less than or equal to the other's end. Sort intervals by start time, then iterate through them, merging overlapping intervals into a result list. Finally, return the merged list, which will be sorted by start time.
Pro tip: Mention edge cases like empty input, single interval, and intervals that touch at endpoints (e.g., [1,2] and [2,3] should merge because they are closed). Also, discuss time complexity: O(m log m) due to sorting, which is optimal.
Ask if intervals are closed (inclusive endpoints) and if the input can be empty or unsorted. Confirm that merging should combine intervals that overlap or touch.
Sort the intervals by their start times. This ensures that any overlapping intervals are adjacent, simplifying the merging process.
Initialize a result list with the first interval. Iterate through the sorted intervals; if the current interval overlaps with the last interval in the result (i.e., its start <= last end), merge them by updating the last interval's end to the maximum of both ends. Otherwise, add the current interval to the result.
After processing all intervals, return the merged list. It will be sorted by start time because we sorted initially and only appended non-overlapping intervals.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.