← Warner Bros Discovery Interview Insights
Start by clarifying the problem: array rotation by k positions, where k can exceed the array length, so normalize k using k % n. Then present an efficient in-place reversal algorithm (O(n) time, O(1) space) for both left and right rotations, explaining the steps clearly. If time permits, mention alternative approaches like using a temporary array or juggling algorithm, but emphasize the reversal method for its simplicity and optimality.
Pro tip: Demonstrate awareness of edge cases (empty array, k=0, k multiple of n) and discuss how to handle them gracefully. Also, mention that the reversal approach can be easily adapted for both left and right rotations by adjusting the reversal order, showing versatility.
Confirm the problem requirements: rotation direction, in-place vs. extra space, and handle k > n by setting k = k % n. If n=0, return immediately.
Select the reversal algorithm for O(n) time and O(1) space. Explain that it works by reversing parts of the array and then the whole array.
For left rotation by k: reverse the first k elements, reverse the remaining n-k elements, then reverse the entire array. Provide a concrete example to illustrate.
For right rotation by k: reverse the entire array, then reverse the first k elements, then reverse the remaining n-k elements. Alternatively, note that right rotation by k is equivalent to left rotation by n-k.
State time complexity O(n) and space O(1). Discuss edge cases: k=0, k=n, empty array, and large k. Mention that the algorithm handles duplicates and works for any data type.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
This one took me longer than it should have.
Clarify the CSV parsing requirements (e.g., quoting, escaping, delimiters) and define what constitutes a match (case sensitivity, whole word vs substring). Then outline an algorithm that parses the CSV into rows and cells while tracking character offsets, and searches each cell for the keyword, recording row, column, and character position. Discuss trade-offs between a simple split-based approach and a robust state-machine parser.
Pro tip: Mention that you would use a proper CSV parser or implement a state machine to handle quoted fields and embedded commas, because naive splitting fails on real-world data. Also, clarify whether the character position is relative to the cell or the entire row, as this ambiguity often trips up candidates.
Ask about CSV format specifics (delimiter, quoting, escaping, newlines in cells) and match semantics (case sensitivity, overlapping matches, whole word). Confirm the definition of row, column, and character position.
Decide between a simple split-based approach (if input is guaranteed simple) or a robust state-machine parser that handles quotes and escapes. Explain the trade-offs and justify your choice.
Iterate through each cell, search for the keyword (e.g., using indexOf in a loop), and record the row index, column index, and character offset within the cell. Handle multiple occurrences per cell.
Write pseudocode or code, then walk through a sample CSV with edge cases (quoted fields, keyword spanning cells, etc.) to verify correctness and discuss time/space complexity.
Mention how to handle large files (streaming), case-insensitive search, or returning results in a structured format (e.g., list of objects). Optionally discuss using regex for complex patterns.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.