← BlackRock Interview Insights
They said I didn't need to write full code, just explain the algorithm clearly.
Start by clarifying the problem: intervals are inclusive, input may be unsorted, and output should be merged. Then propose sorting by start time and iterating to merge overlapping intervals, analyzing time and space complexity.
Pro tip: Mention edge cases like empty input, single interval, and intervals that only touch at endpoints (e.g., [1,2] and [2,3] may or may not merge depending on definition). Also, discuss whether the input can be modified and if stability matters.
Ask about interval inclusivity, whether input can be modified, and expected output format. Confirm handling of empty input, single interval, and touching intervals.
Sort intervals by start time, then iterate and merge if the current interval overlaps with the last merged interval. This yields O(n log n) time due to sorting.
Write clean code, using a result list. Test with provided examples and edge cases like [[1,4],[4,5]] to verify merge condition.
State time complexity O(n log n) and space complexity O(n) for the output (or O(1) extra if sorting in-place and output not counted). Discuss if a linear-time solution is possible with assumptions.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
This is where it got real, they wanted actual code or tight pseudocode, not just hand-waving.
First, clarify the problem constraints and edge cases, then propose a linear scan approach that inserts the new interval in the correct position and merges overlapping intervals. Walk through the algorithm step-by-step, analyze time and space complexity, and discuss potential optimizations or trade-offs.
Pro tip: Mention that since the intervals are sorted and non-overlapping, we can solve this in O(n) time by scanning once, which is optimal. Also, highlight that this approach is efficient for large datasets and can be easily adapted for streaming scenarios.
Ask clarifying questions about input format, interval inclusivity, and expected output. Confirm that intervals are sorted and non-overlapping.
Describe a three-phase approach: add all intervals ending before the new interval starts, merge overlapping intervals with the new interval, then add the remaining intervals.
Trace the algorithm on a sample input to demonstrate correctness and edge cases, such as inserting at the beginning, end, or merging multiple intervals.
State that the time complexity is O(n) and space complexity is O(n) for the output, which is optimal since we must examine each interval at least once.
Mention alternative approaches like binary search for insertion point (still O(n) due to merging) and discuss how to handle unsorted intervals or streaming data.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.