How do you solve Find the Array Concatenation Value on LeetCode?

Find the Array Concatenation Value (LeetCode #2562) can be solved using Brute Force or Optimal Solution. The optimal approach is Optimal Solution with O(n) time complexity and O(1) space complexity. Key insight: Concatenation can be treated as string manipulation, which can be optimized by avoiding unnecessary conversions.

What is the time complexity of Find the Array Concatenation Value?

The optimal solution for Find the Array Concatenation Value runs in O(n) time and uses O(1) space. The time complexity is O(n) because we only loop through the array once, performing constant-time operations for each pair of elements.

What is the brute force solution for Find the Array Concatenation Value?

The brute force approach for Find the Array Concatenation Value is Brute Force, with O(n²) time complexity and O(1) space complexity. The brute-force approach involves repeatedly concatenating the first and last elements of the array until it is empty. This method is straightforward but inefficient due to repeated string conversions. The optimal Optimal Solution approach improves this to O(n).

What algorithm or data structure is used to solve Find the Array Concatenation Value?

Find the Array Concatenation Value uses the following concepts: Array, Two Pointers, Simulation. The recommended patterns to study are: Two Pointers, Simulation.

What are the interview tips for Find the Array Concatenation Value?

Always consider edge cases, such as empty arrays or arrays with one element. Explain your thought process clearly while coding; it shows your understanding. Practice dry-running your solution with sample inputs before finalizing it.

What are common mistakes when solving Find the Array Concatenation Value?

Not handling the case of odd-length arrays correctly. Overcomplicating the solution by using unnecessary data structures.

#2562

Find the Array Concatenation Value

Easy

ArrayTwo PointersSimulationTwo PointersSimulation

LeetCode ↗

Approaches

Brute ForceOptimal

Complexity Comparison

	Brute Force	Optimal Solution★
Time	O(n²)	O(n)
Space	O(1)	O(1)

💡

Intuition

Time O(n)Space O(1)

The optimal approach involves calculating the concatenation values directly using a single loop, which avoids unnecessary array manipulations and string conversions.

⚙️

Algorithm

5 steps

1Step 1: Initialize a variable `concatenation_value` to 0.
2Step 2: Determine the length of the array `n`.
3Step 3: Loop through the first half of the array (0 to n/2) and concatenate the elements at index `i` and `n-i-1`.
4Step 4: If there's a middle element (for odd length), add it directly to `concatenation_value`.
5Step 5: Return `concatenation_value`.

solution.py13 lines

1# Full working Python code
2
3def find_concatenation_value(nums):
4    concatenation_value = 0
5    n = len(nums)
6    for i in range(n // 2):
7        concatenation_value += int(str(nums[i]) + str(nums[n - i - 1]))
8    if n % 2 == 1:
9        concatenation_value += nums[n // 2]
10    return concatenation_value
11
12# Example usage
13print(find_concatenation_value([7, 52, 2, 4]))  # Output: 596

ℹ

Complexity note: The time complexity is O(n) because we only loop through the array once, performing constant-time operations for each pair of elements.

1Concatenation can be treated as string manipulation, which can be optimized by avoiding unnecessary conversions.
2Understanding the structure of the problem allows for more efficient solutions.

Solutions and explanations are original Tejav content. Problem titles © LeetCode — use the LeetCode button above for the full problem statement.