Started fine with BFS for shortest paths and backtracking to reconstruct all sequences.
Start by explaining the standard BFS + DFS approach for Word Ladder II, focusing on building a graph of shortest paths and then backtracking to find all sequences. Then, for the constraint of no common data structures, describe how you would simulate queues, maps, and lists using arrays and manual indexing, and discuss the trade-offs in time and space complexity.
Pro tip: Emphasize that the core challenge is not just solving the problem but demonstrating adaptability and deep understanding of data structures by re-implementing them from scratch. Also, mention that you would discuss with the interviewer whether the constraint applies to the entire solution or just the main algorithm, as this shows pragmatism.
Confirm the exact constraints: whether the 'no common data structures' rule applies to the entire solution or just the core algorithm, and whether auxiliary structures like arrays are allowed. Also, clarify input/output formats and edge cases.
Describe the optimal BFS + DFS approach: use BFS to find the shortest distance from start to end and build a graph of predecessors, then use DFS to reconstruct all shortest paths. Mention time and space complexity.
Explain how to replace queues, maps, and lists with arrays and manual indexing. For example, use an array as a queue with head/tail pointers, use parallel arrays for mapping words to indices, and use arrays for adjacency lists.
Analyze the impact on performance and code complexity: arrays may lead to slower lookups (O(n) instead of O(1)), increased memory usage, and more error-prone code. Discuss whether the constraint is practical and how you would mitigate issues.
Walk through a small example to demonstrate correctness, and discuss how you would test edge cases like no path, multiple paths, and large inputs. Mention potential optimizations within the constraints.
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