The "Similar String Groups" interview question is a sophisticated challenge involving string manipulation and graph theory. Two strings are considered "similar" if they are equal or if you can swap exactly two letters in one string to get the other. A "group" is formed by strings that are directly or indirectly similar (connected components). The "Similar String Groups coding problem" asks you to determine the total number of such disjoint groups in a given list of strings.
This problem is frequently used by top-tier companies like Apple, Meta, and Google because it tests the integration of multiple data structures and algorithms. Candidates must efficiently determine similarity (string manipulation) and then group the strings (graph connectivity). It assesses your ability to handle "HARD" level complexity where the naive solution (comparing every pair of strings) might be slow, and you need to choose between Union-Find, BFS, or DFS based on the constraints.
This is a classic "Union Find, Breadth-First Search, or Depth-First Search interview pattern". Each string can be viewed as a node in a graph. An edge exists between two nodes if the strings are similar. The problem then becomes finding the number of connected components in this graph. If the number of strings is small, an O(N^2 * L) approach (where N is the number of strings and L is the length of each string) is usually acceptable. You iterate through all pairs, check similarity, and perform a union operation in a Disjoint Set Union (DSU) structure.
Consider the list: ["tars", "rats", "arts", "star"].
["abc", "def"], they would be in 2 separate groups.A common mistake is an inefficient similarity check. To check if two strings are similar, you should count the number of positions where the characters differ. If the count is 0 or 2 (and the characters at those 2 positions are the same just swapped), they are similar. Another mistake is using a simple BFS/DFS without considering the potential for a very dense graph, which can lead to Time Limit Exceeded (TLE) if not implemented carefully. Forgetting to handle the "equal strings" case is also a minor but frequent oversight.
Mastering the Union-Find (DSU) data structure is crucial for "Similar String Groups interview question" and similar connectivity problems. Practice implementing DSU with "path compression" and "union by rank" to ensure near-constant time operations. Also, always analyze the constraints: if the number of strings is much larger than the length of strings, your approach might need to shift from comparing pairs to generating all possible "similar" variations.
| Title | Difficulty | Topics | LeetCode |
|---|---|---|---|
| Sentence Similarity II | Medium | Solve | |
| Accounts Merge | Medium | Solve | |
| Smallest String With Swaps | Medium | Solve | |
| Minimize Malware Spread | Hard | Solve | |
| Minimize Malware Spread II | Hard | Solve |