Classic backtracking problem, I knew the shape of the solution pretty quickly.
Use depth-first search (DFS) with backtracking to explore all possible paths from each cell that matches the first character. At each step, check if the current cell matches the next character, mark it as visited, recursively explore its neighbors, then unmark it to allow other paths. Return true if any path matches the entire word.
Pro tip: Optimize by checking if the word's length exceeds the grid size or if the frequency of any character in the word exceeds its frequency in the grid, returning false early. Also, consider using a visited set or modifying the grid in-place to save space.
Confirm edge cases: empty grid, empty word, word longer than grid cells, and character frequency constraints. Discuss assumptions with the interviewer.
Select DFS with backtracking as the primary approach. Mention alternative approaches like BFS but highlight DFS's suitability for path exploration.
Write a recursive function that takes current position and index in word. Check bounds, character match, and visited status. Mark visited, explore four directions, then unmark.
Add early termination checks (e.g., word length > m*n, character frequency). Use in-place marking (e.g., replace with '#') to save space, restoring after backtrack.
State time complexity O(m*n*4^L) where L is word length, and space O(L) for recursion. Walk through a small example and test edge cases.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Start by clarifying the problem context (e.g., grid-based traversal, graph marking) and then explain how to mark visited cells in-place by modifying the input matrix (e.g., flipping signs, using sentinel values, or bitwise operations). Then analyze time and space complexity, emphasizing that space is O(1) auxiliary beyond the input.
Pro tip: Mention that in-place modification may not be acceptable if the input must be preserved, and offer to restore the matrix afterward or discuss trade-offs with the interviewer.
Ask whether the matrix can be mutated and if the original state needs to be restored. Confirm the traversal pattern (e.g., DFS, BFS) and what 'visited' means.
Select a method like negating values, adding a large offset, or using a separate bit (if values allow). Ensure the marker is distinguishable from original values.
During traversal, check if a cell is marked to avoid revisiting. Mark cells as visited before recursing or enqueuing.
Time: O(M×N) for visiting each cell once. Space: O(1) auxiliary if recursion stack is ignored; otherwise O(M×N) for stack in worst case.
If needed, restore the matrix after traversal. Discuss pros (memory savings) and cons (mutating input, potential overflow).
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.