How should I practice Meta Copy List with Random Pointer?

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Meta Copy List with Random Pointer

Meta● MediumFULLTIMEPHONE SCREENONSITE INTERVIEW

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Problem statement

A linked list has n nodes in next-pointer order. Each node contains an integer value and a random pointer that may target any node or be null.

The list is encoded by nodes, where nodes[i] = [value, randomIndex]. The next pointer of node i targets node i + 1, except for the last node. A randomIndex of -1 means null.

Create a deep copy whose next and random pointers target only copied nodes. Preserve the original next-pointer chain after copying. For this exercise, after copying, mutate the original node at mutationIndex: set its value to newValue and its random pointer to newRandomIndex.

Return two encoded snapshots in order: the mutated original list, then the unchanged deep copy.

For an empty list, use mutationIndex = -1 and newRandomIndex = -1; return two empty snapshots.

Function

copyAndMutateRandomList(nodes: int[][], mutationIndex: int, newValue: int, newRandomIndex: int) → int[][][]

Examples

Example 1

nodes = [[7,-1],[13,0],[11,4],[10,2],[1,0]]mutationIndex = 1newValue = 130newRandomIndex = 4return = [[[7,-1],[130,4],[11,4],[10,2],[1,0]],[[7,-1],[13,0],[11,4],[10,2],[1,0]]]

The second original node changes to [130,4]. The second copied node remains [13,0], so the copy is independent.

Example 2

nodes = [[1,1],[2,1]]mutationIndex = 0newValue = 10newRandomIndex = -1return = [[[10,-1],[2,1]],[[1,1],[2,1]]]

The first original node loses its random pointer. The copy retains both original random references.

Example 3

nodes = [[5,0]]mutationIndex = 0newValue = 6newRandomIndex = -1return = [[[6,-1]],[[5,0]]]

The one-node copy keeps its self-random pointer even after the original is changed.

Example 4

nodes = []mutationIndex = -1newValue = 0newRandomIndex = -1return = [[],[]]

An empty list has no node to copy or mutate, so both snapshots are empty.

Constraints

0 <= nodes.length <= 10^4.
Every row of nodes contains exactly two integers.
-10^9 <= nodes[i][0], newValue <= 10^9.
For a nonempty list, every random index and newRandomIndex is -1 or an index from 0 through nodes.length - 1. For an empty list, newRandomIndex = -1.
For a nonempty list, 0 <= mutationIndex < nodes.length. For an empty list, mutationIndex = -1.