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Use depth-first search (DFS) with backtracking to explore all possible paths from each cell that matches the first character of the word. At each step, mark the current cell as visited, recurse in four directions, and then unmark it to allow other paths. Return true if any path matches the entire word.
Pro tip: Mention that you can optimize by checking if the word's length exceeds the number of cells, and if the word contains characters not present in the grid, return false early. Also, discuss pruning by comparing character frequencies.
Confirm the grid dimensions, character set, and whether the word can be empty. Check edge cases like empty grid or word longer than total cells.
Select DFS with backtracking as the primary approach. Explain why BFS is less suitable due to the need to track visited cells per path.
Iterate over each cell; if it matches the first character, start DFS. In DFS, mark the cell visited, explore neighbors, and unmark when backtracking.
Add early termination: if word length > grid cells, return false. Pre-check character frequencies. Optionally, search from the less frequent end of the word.
State time complexity O(N * 3^L) where N is number of cells and L is word length, and space complexity O(L) for recursion stack.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Start by clarifying the problem and walking through a small example to ensure understanding. Then propose an efficient solution, such as using two pointers or precomputed max arrays, and analyze its time and space complexity. Be prepared to discuss trade-offs between different approaches.
Pro tip: Mention that the two-pointer approach achieves O(n) time and O(1) space, which is optimal, and explain why it works by maintaining left_max and right_max. This shows you can optimize beyond the typical O(n) space solution.
Ask clarifying questions about input constraints, edge cases (e.g., empty array, negative heights), and expected output. Confirm that water is trapped between bars and cannot be stored outside the array.
Discuss brute force (O(n^2)), dynamic programming with precomputed max arrays (O(n) time, O(n) space), and the optimal two-pointer approach (O(n) time, O(1) space). Explain the intuition behind each.
Walk through the two-pointer algorithm step by step: initialize left and right pointers, maintain left_max and right_max, and accumulate water based on the smaller max. Use a small example to illustrate.
State that the two-pointer solution runs in O(n) time and O(1) space, which is optimal. Compare with the DP approach that uses O(n) space, and discuss when the extra space might be acceptable.
Mention edge cases like empty array, single bar, strictly increasing/decreasing heights, and all equal heights. Suggest testing with these cases to ensure correctness.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.