
    Design a fraud detection algorithm that determines the number of possible legitimate transaction sequences, where a transaction category can appear consecutively at most twice in a sequence of n transactions across k merchant categories. A sequence is considered potentially fraudulent if the same transaction category appears more than twice in a row, and the algorithm needs to count all non-fraudulent sequence possibilities to establish baseline normal behavior patterns.
    

    
def count_no_of_ways(n, k):
    """
    Design a fraud detection algorithm that determines the number of possible legitimate transaction sequences, where a transaction category can appear consecutively at most twice in a sequence of n transactions across k merchant categories. A sequence is considered potentially fraudulent if the same transaction category appears more than twice in a row, and the algorithm needs to count all non-fraudulent sequence possibilities to establish baseline normal behavior patterns.
    

    """
def count_no_of_ways(n, k):
    """
    Design a fraud detection algorithm that determines the number of possible legitimate transaction sequences, where a transaction category can appear consecutively at most twice in a sequence of n transactions across k merchant categories. A sequence is considered potentially fraudulent if the same transaction category appears more than twice in a row, and the algorithm needs to count all non-fraudulent sequence possibilities to establish baseline normal behavior patterns.
    

    """
    dp = [0] * (n + 1)
    total = k
    mod = 1000000007
    dp[1] = k
    dp[2] = k * k
    for i in range(3, n + 1):
        dp[i] = (k - 1) * (dp[i - 1] + dp[i - 2]) % mod
    return dp[n]