Deep Copy

Subtitle / Summary Clone Graph is not a traversal-only problem. The real challenge is preserving graph structure while avoiding duplicate copies in the presence of cycles. The stable solution is a traversal plus a hash map from original nodes to cloned nodes. Reading time: 12-15 min Tags: graph, dfs, bfs, hash map, deep copy SEO keywords: Clone Graph, graph deep copy, DFS, BFS, LeetCode 133 Meta description: Deep-copy an undirected graph with a node-to-node map, explaining why memoization is mandatory and how DFS/BFS versions work, with runnable code in six languages. Target Readers LeetCode learners practicing graph traversal and deep-copy patterns Engineers who duplicate object graphs, workflow graphs, or topology graphs Developers who want one reusable template for “clone with cycles” Background / Motivation Many “copy” problems are actually identity-preservation problems. ...

Subtitle / Abstract The real challenge in this problem is not traversing the list, but correctly cloning the cross-node reference relationships created by random pointers. This article moves from naive intuition to a hash-mapping solution, and explains why it is stable, maintainable, and practical in real engineering. Estimated reading time: 12–16 minutes Tags: Linked List, Deep Copy, Hash Table, Random Pointer SEO keywords: LeetCode 138, Copy List with Random Pointer, random list copy, deep copy, hash mapping Meta description: Perform deep copy of a random-pointer linked list via two passes plus a mapping table, with correctness, complexity, engineering practice, and six-language implementations. Target Readers Developers who feel shaky on random pointer problems while practicing LeetCode Learners who want to clearly understand “shallow copy vs deep copy” Engineers who want to transfer algorithmic thinking to real object-copy scenarios Background / Motivation For a normal linked list, copying val and next is straightforward. A random-pointer list adds one more pointer, random, which can: ...