Is Array Transformation easy or hard?

Array Transformation is classified as an Easy problem. The logic is straightforward once you recognize that the task is a simulation problem and that updates must be applied simultaneously using a separate array.

Array Transformation Python/Java solution

Implement a loop that repeatedly scans indices 1 through n-2 and writes updates into a new array. After each pass, replace the original array with the updated one and continue until no values change. The same logic works in Python, Java, C++, and Go.

How to solve Array Transformation in O(n)?

The entire process cannot be guaranteed in strict O(n) time because multiple transformation rounds may occur. The optimal strategy is O(n * k) simulation, where each round scans the array once. Early termination when no changes occur keeps the number of rounds small in practice.

What is the best approach for Array Transformation?

The best approach is simulation. Iterate through the array, compute a new array for the next state, and update values that are local minima or maxima. Because all updates must occur simultaneously, using a copied array is required. The process repeats until a full pass produces no changes.

Is Array Transformation asked at Google/Amazon/Meta?

Array Transformation represents a common interview pattern involving simulation and state transitions. Variations of array stabilization and iterative updates appear in interviews at large tech companies. The problem tests careful handling of simultaneous updates and array traversal logic.

What data structure is used in Array Transformation?

The solution primarily uses a standard array along with an auxiliary copy of the array for the next state. The copy ensures that all updates are applied simultaneously without affecting comparisons during the same iteration.

What is the time complexity of Array Transformation?

The time complexity is O(n * k), where n is the array length and k is the number of transformation rounds before the array stabilizes. Each round scans the array once. Space complexity is O(n) because a copy of the array is used to apply simultaneous updates.

1243. Array Transformation - Practice Online

Given an initial array arr, every day you produce a new array using the array of the previous day.

On the i-th day, you do the following operations on the array of day i-1 to produce the array of day i:

If an element is smaller than both its left neighbor and its right neighbor, then this element is incremented.
If an element is bigger than both its left neighbor and its right neighbor, then this element is decremented.
The first and last elements never change.

After some days, the array does not change. Return that final array.

Example 1:

Input: arr = [6,2,3,4]
Output: [6,3,3,4]
Explanation: 
On the first day, the array is changed from [6,2,3,4] to [6,3,3,4].
No more operations can be done to this array.

Example 2:

Input: arr = [1,6,3,4,3,5]
Output: [1,4,4,4,4,5]
Explanation: 
On the first day, the array is changed from [1,6,3,4,3,5] to [1,5,4,3,4,5].
On the second day, the array is changed from [1,5,4,3,4,5] to [1,4,4,4,4,5].
No more operations can be done to this array.

Constraints:

3 <= arr.length <= 100
1 <= arr[i] <= 100