LeetCode #1389 — EASY

Create Target Array in the Given Order

Build confidence with an intuition-first walkthrough focused on array fundamentals.

Solve on LeetCode

The Problem

Problem Statement

Given two arrays of integers nums and index. Your task is to create target array under the following rules:

Initially target array is empty.
From left to right read nums[i] and index[i], insert at index index[i] the value nums[i] in target array.
Repeat the previous step until there are no elements to read in nums and index.

Return the target array.

It is guaranteed that the insertion operations will be valid.

Example 1:

Input: nums = [0,1,2,3,4], index = [0,1,2,2,1]
Output: [0,4,1,3,2]
Explanation:
nums       index     target
0            0        [0]
1            1        [0,1]
2            2        [0,1,2]
3            2        [0,1,3,2]
4            1        [0,4,1,3,2]

Example 2:

Input: nums = [1,2,3,4,0], index = [0,1,2,3,0]
Output: [0,1,2,3,4]
Explanation:
nums       index     target
1            0        [1]
2            1        [1,2]
3            2        [1,2,3]
4            3        [1,2,3,4]
0            0        [0,1,2,3,4]

Example 3:

Input: nums = [1], index = [0]
Output: [1]

Constraints:

1 <= nums.length, index.length <= 100
nums.length == index.length
0 <= nums[i] <= 100
0 <= index[i] <= i

Step 01

Brute Force Baseline

Problem summary: Given two arrays of integers nums and index. Your task is to create target array under the following rules: Initially target array is empty. From left to right read nums[i] and index[i], insert at index index[i] the value nums[i] in target array. Repeat the previous step until there are no elements to read in nums and index. Return the target array. It is guaranteed that the insertion operations will be valid.

Baseline thinking

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

Pattern signal: Array

Example 1

[0,1,2,3,4]
[0,1,2,2,1]

Example 2

[1,2,3,4,0]
[0,1,2,3,0]

Example 3

[1]
[0]

Step 02

Core Insight

What unlocks the optimal approach

Simulate the process and fill corresponding numbers in the designated spots.

Interview move: turn each hint into an invariant you can check after every iteration/recursion step.

Step 03

Algorithm Walkthrough

Iteration Checklist

Define state (indices, window, stack, map, DP cell, or recursion frame).
Apply one transition step and update the invariant.
Record answer candidate when condition is met.
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 #1389: Create Target Array in the Given Order
class Solution {
    public int[] createTargetArray(int[] nums, int[] index) {
        int n = nums.length;
        List<Integer> target = new ArrayList<>();
        for (int i = 0; i < n; ++i) {
            target.add(index[i], nums[i]);
        }
        // return target.stream().mapToInt(i -> i).toArray();
        int[] ans = new int[n];
        for (int i = 0; i < n; ++i) {
            ans[i] = target.get(i);
        }
        return ans;
    }
}

// Accepted solution for LeetCode #1389: Create Target Array in the Given Order
func createTargetArray(nums []int, index []int) []int {
	target := make([]int, len(nums))
	for i, x := range nums {
		copy(target[index[i]+1:], target[index[i]:])
		target[index[i]] = x
	}
	return target
}

# Accepted solution for LeetCode #1389: Create Target Array in the Given Order
class Solution:
    def createTargetArray(self, nums: List[int], index: List[int]) -> List[int]:
        target = []
        for x, i in zip(nums, index):
            target.insert(i, x)
        return target

// Accepted solution for LeetCode #1389: Create Target Array in the Given Order
struct Solution;

impl Solution {
    fn create_target_array(nums: Vec<i32>, index: Vec<i32>) -> Vec<i32> {
        let mut res = vec![];
        let n = nums.len();
        for i in 0..n {
            let e = nums[i];
            let j = index[i] as usize;
            res.insert(j, e);
        }
        res
    }
}

#[test]
fn test() {
    let nums = vec![0, 1, 2, 3, 4];
    let index = vec![0, 1, 2, 2, 1];
    let res = vec![0, 4, 1, 3, 2];
    assert_eq!(Solution::create_target_array(nums, index), res);
    let nums = vec![1, 2, 3, 4, 0];
    let index = vec![0, 1, 2, 3, 0];
    let res = vec![0, 1, 2, 3, 4];
    assert_eq!(Solution::create_target_array(nums, index), res);
    let nums = vec![1];
    let index = vec![0];
    let res = vec![1];
    assert_eq!(Solution::create_target_array(nums, index), res);
}

// Accepted solution for LeetCode #1389: Create Target Array in the Given Order
function createTargetArray(nums: number[], index: number[]): number[] {
    const ans: number[] = [];
    for (let i = 0; i < nums.length; i++) {
        ans.splice(index[i], 0, nums[i]);
    }
    return ans;
}

Step 06

Interactive Study Demo

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

Custom checkpoints (one per line)

Press Step or Run All to begin.

Step 07

Complexity Analysis

Time

O(n^2)

Space

O(n)

Approach Breakdown

BRUTE FORCE

O(n²) time

O(1) space

Two nested loops check every pair or subarray. The outer loop fixes a starting point, the inner loop extends or searches. For n elements this gives up to n²/2 operations. No extra space, but the quadratic time is prohibitive for large inputs.

OPTIMIZED

O(n) time

O(1) space

Most array problems have an O(n²) brute force (nested loops) and an O(n) optimal (single pass with clever state tracking). The key is identifying what information to maintain as you scan: a running max, a prefix sum, a hash map of seen values, or two pointers.

Shortcut: If you are using nested loops on an array, there is almost always an O(n) solution. Look for the right auxiliary state.

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.