Not too bad once you map each character to its position index and compare adjacent words character by character.
First, clarify the problem and edge cases, then propose a solution that compares adjacent strings using the custom alphabet order. Discuss the time complexity and potential optimizations, and be prepared to code the comparison logic.
Pro tip: Mention that you can precompute a rank map for O(1) character comparisons, and handle the tricky case where one string is a prefix of another (shorter string should come first).
Confirm the definition of nondecreasing lexicographic order with the custom alphabet, and ask about edge cases like empty strings, duplicate strings, and characters not in the alphabet.
Create a function that compares two strings character by character using the custom order, returning -1, 0, or 1. Use a hash map to store the rank of each character for O(1) lookups.
Iterate through the list and compare each pair of adjacent strings using the comparison function. If any pair is out of order, return false; otherwise, return true.
Explain that the time complexity is O(N * L) where N is the number of strings and L is the average length, and space complexity is O(1) extra aside from the rank map.
Walk through test cases including edge cases, and discuss potential optimizations like early termination or parallel comparison if needed.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
This is basically topological sort and I knew that, but I fumbled the graph construction phase more than I'd like to admit.
Model the problem as a directed graph where each character is a node and edges represent ordering constraints derived from adjacent words. Then perform a topological sort to find a valid alphabet order, detecting cycles to determine impossibility. Handle edge cases like invalid prefixes and duplicate words.
Pro tip: Emphasize that the graph approach is optimal (O(N) time) and discuss how to handle edge cases like when a shorter word appears after a longer word with the same prefix, which immediately makes the ordering impossible.
Iterate through adjacent word pairs and find the first differing character to create a directed edge from the earlier character to the later one. If no differing character exists and the first word is longer, return impossible.
Represent the graph using an adjacency list and track in-degrees for each character. Include all unique characters from the list as nodes.
Use Kahn's algorithm or DFS to generate a topological ordering. If the ordering doesn't include all characters, a cycle exists, so return impossible.
Output the topological order as a string. If multiple valid orders exist, any one is acceptable.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.