What is the best way to approach 'Create Target Array in the Given Order'?

Iterate through nums and index simultaneously, inserting each value at its corresponding position using array insert operations.

Why is this problem considered an array plus simulation pattern?

Because the solution involves simulating the insertion process step by step, updating the array dynamically as you go.

Can I use a linked list to solve this problem?

Yes, a linked list can reduce shifting cost for large arrays, but it may complicate random access compared to standard arrays.

What are common mistakes to avoid?

Overwriting elements instead of shifting, ignoring order of operations, and assuming indexes are pre-sorted.

What is the time complexity for this simulation approach?

O(n^2) due to repeated shifting of elements during insertions, with O(n) space to store the target array.

#1389

Easy

auto_awesome数组·模拟

LeetCode 题解工作台

按既定顺序创建目标数组

给你两个整数数组 nums 和 index 。你需要按照以下规则创建目标数组：目标数组 target 最初为空。按从左到右的顺序依次读取 nums[i] 和 index[i] ，在 target 数组中的下标 index[i] 处插入值 nums[i] 。重复上一步，直到在 nums 和 in…

数组模拟

题目描述

给你两个整数数组 nums 和 index。你需要按照以下规则创建目标数组：

目标数组 target 最初为空。
按从左到右的顺序依次读取 nums[i] 和 index[i]，在 target 数组中的下标 index[i] 处插入值 nums[i] 。
重复上一步，直到在 nums 和 index 中都没有要读取的元素。

请你返回目标数组。

题目保证数字插入位置总是存在。

示例 1：

输入：nums = [0,1,2,3,4], index = [0,1,2,2,1]
输出：[0,4,1,3,2]
解释：
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]

示例 2：

输入：nums = [1,2,3,4,0], index = [0,1,2,3,0]
输出：[0,1,2,3,4]
解释：
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]

示例 3：

输入：nums = [1], index = [0]
输出：[1]

提示：

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

lightbulb

解题思路

方法一：模拟

我们创建一个列表 $target$ ，用于存储目标数组。由于题目保证数字插入位置总是存在，因此我们可以直接按照给定的顺序插入到对应的位置。

时间复杂度 $O(n^2)$ ，空间复杂度 $O(n)$ 。其中 $n$ 是数组的长度。

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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

speed

复杂度分析

指标	值
时间	complexity is O(n^2) for array insertions due to shifting elements, while space complexity is O(n) for storing the target array.
空间	Depends on the final approach

psychology

面试官常问的追问

外企场景

question_mark
Look for correct handling of index-based insertions without overwriting existing elements.
question_mark
Expect candidates to simulate array operations rather than attempting complex mathematical formulas.
question_mark
Watch for off-by-one errors when elements need to shift to accommodate new insertions.

warning

常见陷阱

外企场景

error
Overwriting elements instead of shifting them during insertion.
error
Ignoring the correct order of operations, which can produce incorrect target arrays.
error
Assuming indexes are sorted or that insertions do not require dynamic adjustments.

swap_horiz

进阶变体

外企场景

arrow_right_alt
Creating a target array with duplicate values in nums, testing stability of insertions.
arrow_right_alt
Using extremely large arrays to explore time complexity limits of the simulation approach.
arrow_right_alt
Modifying the problem to remove guarantees about valid insertions, requiring bounds checks.

help

常见问题

外企场景

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