Treat the grid as a graph and use DFS/BFS to explore each unvisited land cell, marking all connected land cells as visited. Each time you start a traversal from an unvisited land cell, increment the island count. Alternatively, use Union-Find to merge adjacent 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 vs iterative to avoid stack overflow) and Union-Find (better for dynamic updates). Mention that in ML pipelines, similar connected-component logic is used in image segmentation and clustering.
Confirm grid dimensions, connectivity (4-directional), and whether input can be modified. Ask about edge cases like empty grid or large sizes.
Decide between DFS/BFS (simple, O(mn) time) or Union-Find (good for dynamic connectivity). Explain your choice based on constraints and potential follow-ups.
Describe how you'll iterate through cells, and when encountering an unvisited '1', increment count and traverse all connected '1's, marking them visited (e.g., set to '0' or use a visited matrix).
State time and space complexity (O(mn) time, O(mn) space for visited or recursion stack). Discuss handling of empty grid, single row/column, and large grids.
Mention iterative DFS to avoid recursion limits, Union-Find with path compression, or potential parallelization. Relate to ML applications like connected component labeling in images.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Use a backtracking (DFS) approach to build letter combinations by processing digits one by one, appending mapped letters at each step. Alternatively, use an iterative BFS approach with a queue. After generating all combinations, return the list and its length as the count.
Pro tip: Clarify edge cases upfront: empty input, digits '0' or '1' (which have no letters), and whether the output should be sorted. Also mention that the count is simply the product of the number of letters per digit, but you'll generate the strings anyway.
Ask about input constraints (e.g., string length, valid digits), expected output format (list of strings, count), and handling of '0'/'1' or empty input. Confirm if duplicates or sorting matter.
Create a mapping from digits 2-9 to their corresponding letters (e.g., 2: 'abc', 3: 'def', etc.). Note that 0 and 1 have no letters, so they should be handled as special cases.
Use backtracking: recursively build combinations by iterating over letters for the current digit and recursing to the next. Or use iterative BFS: start with an empty string, and for each digit, append each letter to existing combinations.
Write the code, ensuring that empty input returns an empty list (or list with empty string, depending on definition). If any digit is '0' or '1', return empty list (or skip). Also compute the count as the length of the result list.
Discuss time complexity O(4^n * n) where n is number of digits (since max 4 letters per digit) and space complexity O(n) for recursion stack (or O(4^n) for output). Test with examples like '23', '2345', and edge cases.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.