Use a graph traversal algorithm (DFS or BFS) to explore each unvisited land cell and mark all connected land cells as visited, incrementing the island count for each traversal. Alternatively, use Union-Find to group connected land cells and count distinct sets.
Pro tip: Clarify edge cases upfront (empty grid, all water, all land) and discuss trade-offs between DFS (recursive, may stack overflow) and BFS (iterative, uses queue). Mention that modifying the grid in-place saves space but may not be allowed.
Confirm that islands are connected horizontally or vertically (not diagonally) and that you need to count distinct connected components of 1s.
Decide between DFS, BFS, or Union-Find. DFS/BFS are simpler; Union-Find is efficient for dynamic connectivity but overkill here.
Iterate through each cell; when you find an unvisited '1', increment the count and traverse all connected '1's, marking them as visited (e.g., set to '0' or use a visited matrix).
Time complexity is O(rows * cols) since each cell is visited once. Space complexity is O(rows * cols) in worst case for recursion stack or queue.
Consider empty grid, single cell, all water, all land, and multiple disconnected islands. Walk through a small example to verify.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Clarify the merge semantics and data structures, then propose a recursive solution that traverses both trees simultaneously, merging payloads for matching keys and preserving unmatched subtrees. Discuss time/space complexity and consider iterative alternatives or optimizations for large trees.
Pro tip: Explicitly state your assumptions about payload merging (e.g., deep merge vs. overwrite) and key uniqueness, and mention how you'd handle edge cases like null roots or duplicate keys within a tree.
Ask about payload merge semantics (e.g., overwrite vs. deep merge), key uniqueness, and whether trees are mutable. Confirm input/output expectations and edge cases.
Decide on a representation for N-ary trees (e.g., children list or map keyed by child key) and whether to use recursion or iteration. A map for children enables O(1) key lookup.
Recursively merge nodes: if both exist, merge payloads (B overwrites A) and merge children by key; if only one exists, keep it as-is. Handle base cases for null nodes.
Discuss time complexity O(N+M) where N and M are node counts, and space complexity O(H) for recursion depth. Compare recursive vs. iterative approaches and in-place vs. new tree.
Walk through simple cases (both empty, one empty, matching keys, non-matching keys) and edge cases (deep trees, duplicate keys). Verify correctness and discuss potential optimizations.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.