Use a hash map to store each word along with its index, then for each word, split it at every possible position and check if the prefix/suffix can form a palindrome with another word. Handle edge cases like empty strings and duplicate words carefully.
Pro tip: Clarify whether the two words can be the same index (i.e., i != j) and whether the order matters (i.e., (i, j) and (j, i) are distinct). Also, discuss time complexity trade-offs between brute force and optimized approach.
Confirm that pairs must have distinct indices (i != j) and that order matters (i, j) and (j, i) are different. Consider empty strings, duplicate words, and words that are themselves palindromes.
Iterate over all pairs (i, j) with i != j, concatenate words[i] + words[j], and check if the result is a palindrome. This is O(n^2 * L) where L is the average word length.
Store each word and its index in a hash map. For each word, split it into two parts at every position: prefix and suffix. Check if the prefix is a palindrome and if the reverse of the suffix exists in the map (and is not the same index). Similarly, check if the suffix is a palindrome and if the reverse of the prefix exists.
When checking for the reverse of a part, ensure the index is different. For empty strings, they can pair with any palindrome word, but be careful not to double-count.
The optimized approach runs in O(n * L^2) time and O(n * L) space. Walk through examples like ['bat', 'tab', 'cat'] and edge cases like ['', 'a'] to verify correctness.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Model the problem as a state-space search where each state includes the current position and the set of keys collected. Use BFS to find the shortest path, since all moves have equal cost. Represent the key set as a bitmask to efficiently track progress.
Pro tip: Before coding, clarify constraints like grid size and number of keys; if keys are few (≤10), bitmask BFS is optimal, but if many, consider A* with a heuristic like minimum spanning tree over remaining keys.
Ask about grid dimensions, number of keys, whether locks require specific keys, and if multiple keys can be collected. Confirm that you need the shortest path length, not the actual path.
Use a tuple (row, col, keys_bitmask) to represent the state. The bitmask tracks which keys have been collected, with each bit corresponding to a key.
Start BFS from the initial position with an empty key set. For each move, update the key set if a key is picked up, and only pass through a lock if the corresponding key is held. Use a visited set to avoid revisiting states.
When the key set contains all keys, return the current distance. If BFS exhausts all states without collecting all keys, return -1 or indicate no solution.
Discuss time complexity O(R*C*2^K) and space complexity O(R*C*2^K). Mention possible optimizations like bidirectional BFS or A* if needed.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.