Is Alternating Groups II easy or hard?

Alternating Groups II is rated Medium. The main challenge is handling the circular array and recognizing that a group of k elements depends on k-1 alternating neighbor comparisons. Once that insight is clear, a linear-time sliding window solution becomes straightforward.

Alternating Groups II Python/Java solution

Most implementations iterate through the circular array and maintain a sliding window that tracks alternating edges. The logic is identical across Python, Java, C++, and other languages: update the window state as you move forward and increment the count whenever k tiles satisfy the alternating condition.

How to solve Alternating Groups II in O(n)?

Track whether adjacent tiles alternate and maintain a sliding window representing k consecutive tiles. A group is valid when the window contains exactly k-1 alternating edges. Update the window as you move forward across the circular array using modulo indexing to handle wrap-around.

What is the best approach for Alternating Groups II?

The best approach uses a sliding window to track whether each group of k tiles maintains alternating neighbors. A valid group requires k-1 alternating edges. By updating the window incrementally while traversing the circular array, you count valid groups in O(n) time with O(1) extra space.

Is Alternating Groups II asked at Google/Amazon/Meta?

Alternating pattern and sliding window problems frequently appear in interviews at companies like Amazon, Google, and Meta. While this exact problem may vary, the technique of counting valid windows based on adjacency conditions is a common interview pattern.

What data structure is used in Alternating Groups II?

The core data structure is an array combined with a sliding window technique. Some implementations also use an auxiliary array to store whether adjacent elements alternate, which simplifies pattern detection before applying the window.

What is the time complexity of Alternating Groups II?

The optimal solution runs in O(n) time where n is the number of tiles in the colors array. Each element is processed a constant number of times while maintaining the sliding window. Space complexity can be O(1) with direct window tracking or O(n) if an auxiliary array is used.

Description Hints 2 Solution Video 14:05

3208. Alternating Groups II

Medium59.9% acceptance5 companies

There is a circle of red and blue tiles. You are given an array of integers colors and an integer k. The color of tile i is represented by colors[i]:

colors[i] == 0 means that tile i is red.
colors[i] == 1 means that tile i is blue.

An alternating group is every k contiguous tiles in the circle with alternating colors (each tile in the group except the first and last one has a different color from its left and right tiles).

Return the number of alternating groups.

Note that since colors represents a circle, the first and the last tiles are considered to be next to each other.

Example 1:

Input: colors = [0,1,0,1,0], k = 3

Output: 3

Explanation:

Alternating groups:

Example 2:

Input: colors = [0,1,0,0,1,0,1], k = 6

Output: 2

Explanation:

Alternating groups:

Example 3:

Input: colors = [1,1,0,1], k = 4

Output: 0

Explanation:

Constraints:

3 <= colors.length <= 10⁵
0 <= colors[i] <= 1
3 <= k <= colors.length

Asked at 5 companies

eBay Samsara

Google Microsoft Bloomberg

Topics

Array Sliding Window

Hints open one at a time

Hint 1

Try to find a tile that has the same color as its next tile (if it exists).

Hint 2

Then try to find maximal alternating groups by starting a single for loop from that tile.

14:05

Still stuck?Read 3 approaches, or watch a walkthrough.

Open solution

LanguageLoading editor…

1class Solution:
2    def numberOfAlternatingGroups(self, colors: List[int], k: int) -> int:
3        

Starter codePython 3Spaces: 4

Examples

Case 1Case 2Case 3

Input

[0,1,0,1,0]
3

Input

[0,1,0,0,1,0,1]
6

Input

[1,1,0,1]
4

Your code is saved on this device.Solution