LeetCode #3217 — MEDIUM

Delete Nodes From Linked List Present in Array

Move from brute-force thinking to an efficient approach using array strategy.

Solve on LeetCode
The Problem

Problem Statement

You are given an array of integers nums and the head of a linked list. Return the head of the modified linked list after removing all nodes from the linked list that have a value that exists in nums.

Example 1:

Input: nums = [1,2,3], head = [1,2,3,4,5]

Output: [4,5]

Explanation:

Remove the nodes with values 1, 2, and 3.

Example 2:

Input: nums = [1], head = [1,2,1,2,1,2]

Output: [2,2,2]

Explanation:

Remove the nodes with value 1.

Example 3:

Input: nums = [5], head = [1,2,3,4]

Output: [1,2,3,4]

Explanation:

No node has value 5.

Constraints:

  • 1 <= nums.length <= 105
  • 1 <= nums[i] <= 105
  • All elements in nums are unique.
  • The number of nodes in the given list is in the range [1, 105].
  • 1 <= Node.val <= 105
  • The input is generated such that there is at least one node in the linked list that has a value not present in nums.
Patterns Used

Roadmap

  1. Brute Force Baseline
  2. Core Insight
  3. Algorithm Walkthrough
  4. Edge Cases
  5. Full Annotated Code
  6. Interactive Study Demo
  7. Complexity Analysis
Step 01

Brute Force Baseline

Problem summary: You are given an array of integers nums and the head of a linked list. Return the head of the modified linked list after removing all nodes from the linked list that have a value that exists in nums.

Baseline thinking

Start with the most direct exhaustive search. That gives a correctness anchor before optimizing.

Pattern signal: Array · Hash Map · Linked List

Example 1

[1,2,3]
[1,2,3,4,5]

Example 2

[1]
[1,2,1,2,1,2]

Example 3

[5]
[1,2,3,4]

Related Problems

  • Remove Linked List Elements (remove-linked-list-elements)
  • Delete Node in a Linked List (delete-node-in-a-linked-list)
  • Remove Nodes From Linked List (remove-nodes-from-linked-list)
Step 02

Core Insight

What unlocks the optimal approach

  • Add all elements of <code>nums</code> into a Set.
  • Scan the list to check if the current element should be deleted by checking the Set.
Interview move: turn each hint into an invariant you can check after every iteration/recursion step.
Step 03

Algorithm Walkthrough

Iteration Checklist

  1. Define state (indices, window, stack, map, DP cell, or recursion frame).
  2. Apply one transition step and update the invariant.
  3. Record answer candidate when condition is met.
  4. Continue until all input is consumed.
Use the first example testcase as your mental trace to verify each transition.
Step 04

Edge Cases

Minimum Input
Single element / shortest valid input
Validate boundary behavior before entering the main loop or recursion.
Duplicates & Repeats
Repeated values / repeated states
Decide whether duplicates should be merged, skipped, or counted explicitly.
Extreme Constraints
Upper-end input sizes
Re-check complexity target against constraints to avoid time-limit issues.
Invalid / Corner Shape
Empty collections, zeros, or disconnected structures
Handle special-case structure before the core algorithm path.
Step 05

Full Annotated Code

Source-backed implementations are provided below for direct study and interview prep.

// Accepted solution for LeetCode #3217: Delete Nodes From Linked List Present in Array
/**
 * Definition for singly-linked list.
 * public class ListNode {
 *     int val;
 *     ListNode next;
 *     ListNode() {}
 *     ListNode(int val) { this.val = val; }
 *     ListNode(int val, ListNode next) { this.val = val; this.next = next; }
 * }
 */
class Solution {
    public ListNode modifiedList(int[] nums, ListNode head) {
        Set<Integer> s = new HashSet<>();
        for (int x : nums) {
            s.add(x);
        }
        ListNode dummy = new ListNode(0, head);
        for (ListNode pre = dummy; pre.next != null;) {
            if (s.contains(pre.next.val)) {
                pre.next = pre.next.next;
            } else {
                pre = pre.next;
            }
        }
        return dummy.next;
    }
}
Step 06

Interactive Study Demo

Use this to step through a reusable interview workflow for this problem.

Press Step or Run All to begin.
Step 07

Complexity Analysis

Time
O(n + m)
Space
O(n)

Approach Breakdown

COPY TO ARRAY
O(n) time
O(n) space

Copy all n nodes into an array (O(n) time and space), then use array indexing for random access. Operations like reversal or middle-finding become trivial with indices, but the O(n) extra space defeats the purpose of using a linked list.

IN-PLACE POINTERS
O(n) time
O(1) space

Most linked list operations traverse the list once (O(n)) and re-wire pointers in-place (O(1) extra space). The brute force often copies nodes to an array to enable random access, costing O(n) space. In-place pointer manipulation eliminates that.

Shortcut: Traverse once + re-wire pointers → O(n) time, O(1) space. Dummy head nodes simplify edge cases.
Coach Notes

Common Mistakes

Review these before coding to avoid predictable interview regressions.

Off-by-one on range boundaries

Wrong move: Loop endpoints miss first/last candidate.

Usually fails on: Fails on minimal arrays and exact-boundary answers.

Fix: Re-derive loops from inclusive/exclusive ranges before coding.

Mutating counts without cleanup

Wrong move: Zero-count keys stay in map and break distinct/count constraints.

Usually fails on: Window/map size checks are consistently off by one.

Fix: Delete keys when count reaches zero.

Losing head/tail while rewiring

Wrong move: Pointer updates overwrite references before they are saved.

Usually fails on: List becomes disconnected mid-operation.

Fix: Store next pointers first and use a dummy head for safer joins.