Algorithm: Max Counters

Question

I have the following problem:

You are given N counters, initially set to 0, and you have two possible operations on them:

• increase(X) − counter X is increased by 1,
• max_counter − all counters are set to the maximum value of any counter.

A non-empty zero-indexed array A of M integers is given. This array represents consecutive operations:

• if A[K] = X, such that 1 ≤ X ≤ N, then operation K is increase(X),
• if A[K] = N + 1 then operation K is max_counter.

For example, given integer N = 5 and array A such that:

A[0] = 3
A[1] = 4
A[2] = 4
A[3] = 6
A[4] = 1
A[5] = 4
A[6] = 4

the values of the counters after each consecutive operation will be:

(0, 0, 1, 0, 0)
(0, 0, 1, 1, 0)
(0, 0, 1, 2, 0)
(2, 2, 2, 2, 2)
(3, 2, 2, 2, 2)
(3, 2, 2, 3, 2)
(3, 2, 2, 4, 2)

The goal is to calculate the value of every counter after all operations.

I did the following solution but it runs at O(NK) where K = length of array A.

public int[] solution(int N, int[] A) {
    int[] result = new int[N];
    int maximum = 0;

    for (int K = 0; K < A.Length; K++)
    {
        if (A[K] < 1 || A[K] > N + 1)
            throw new InvalidOperationException();

        if (A[K] >= 1 && A[K] <= N)
        {
            result[A[K] - 1]++;

            if (result[A[K] - 1] > maximum)
            {
                maximum = result[A[K] - 1];
            }
        }
        else
        {
            // inefficiency here
            for (int i = 0; i < result.Length; i++)
                result[i] = maximum;
        }
    }

    return result;
}

Could anyone show me how this can be better done with O(N + K) where K is the length of array A? Sorry for may terrible coding, I am doing these exercises to improve my programming. Thanks!

Answer 1

This is what I came up with, but I am not sure if it works 100%:

public int[] solution(int N, int[] A) {
    int[] result = new int[N];
    int maximum = 0;
    int resetLimit = 0;

    for (int K = 0; K < A.Length; K++)
    {
        if (A[K] < 1 || A[K] > N + 1)
            throw new InvalidOperationException();

        if (A[K] >= 1 && A[K] <= N)
        {
            if (result[A[K] - 1] < resetLimit) {
                result[A[K] - 1] = resetLimit + 1;
            } else {
                result[A[K] - 1]++;
            }

            if (result[A[K] - 1] > maximum)
            {
                maximum = result[A[K] - 1];
            }
        }
        else
        {
            // inefficiency here
            //for (int i = 0; i < result.Length; i++)
            //    result[i] = maximum;
            resetLimit = maximum;
        }
    }

    for (int i = 0; i < result.Length; i++)
        result[i] = Math.Max(resetLimit, result[i]);

    return result;
}

Answer 2

Remember:

"Making your code readable is as important as making it executable."

-- Robert C Martin

Even when trying to solve a hard problem...

So trying to achieve a better readability I've created a class to encapsulate the counters array and its operations (Law of Demeter). Sadly my first solution got only 60% in the performance test, so at the cost of a bit of readability I've improved it with a smarter solution and finally got 100%.

Here are my two implementations with comments:

O(N*M) Correctness 100% / Performance 60% (high redability)

//I didn't refactored the names of the variables N and A
//to maintain it aligned with the question description
public int[] solution(int N, int[] A)
{
    var counters = new Counters(N);

    for (int k = 0; k < A.Length; k++)
    {
        if (A[k] <= N)
            counters.IncreaseCounter(A[k]);
        else
            counters.MaxAllCounters();
    }

    return counters.ToArray();
}

public class Counters
{
    private int[] counters;
    private int greaterValueInCounter = 0;

    public Counters(int length)
    {
        counters = new int[length];
    }

    public void MaxAllCounters()
    {
        for (int i = 0; i < counters.Length; i++)
        {
            counters[i] = greaterValueInCounter;
        }
    }

    public void IncreaseCounter(int counterPosition)
    {
        //The counter is one-based, but our array is zero-based
        counterPosition--;

        //Increments the counter
        counters[counterPosition]++;

        if (counters[counterPosition] > greaterValueInCounter)
            greaterValueInCounter = counters[counterPosition];
    }

    //The counters array is encapsuled in this class so if we provide external 
    //acess to it anyone could modify it and break the purpose of the encapsulation
    //So we just exposes a copy of it :)
    public int[] ToArray()
    {
        return (int[])counters.Clone();
    }
} 

Codility result

O(N+M) Correctness 100% / Performance 100% (not so high redability)

Note the beauty of the encapsulation: to improve the algorithm I just have to edit some methods of the Counters class without changing a single character on the solution method.

Methods edited in the Counters class:

• IncreaseCounter()
• MaxAllCounters()
• ToArray()

Final code:

//Exactly the same code
public int[] solution(int N, int[] A)
{
    var counters = new Counters(N);

    for (int k = 0; k < A.Length; k++)
    {
        if (A[k] <= N)
            counters.IncreaseCounter(A[k]);
        else
            counters.MaxAllCounters();
    }

    return counters.ToArray();
}

public class Counters
{
    private int[] counters;
    private int greaterValueInCounter = 0;
    private int currentEquilibratedScore = 0;

    public Counters(int length)
    {
        counters = new int[length];
    }

    public void MaxAllCounters()
    {
        //We don't update the entire array anymore - that was what caused the O(N*M)
        //We just save the current equilibrated score value
        currentEquilibratedScore = greaterValueInCounter;
    }

    public void IncreaseCounter(int counterPosition)
    {
        //The counter is one-based, but our array is zero-based
        counterPosition--;

        //We need to add this "if" here because with this new solution the array
        //is not always updated, so if we detect that this position is lower than
        //the currentEquilibratedScore, we update it before any operation
        if (counters[counterPosition] < currentEquilibratedScore)
            counters[counterPosition] = currentEquilibratedScore + 1;
        else
            counters[counterPosition]++;

        if (counters[counterPosition] > greaterValueInCounter)
            greaterValueInCounter = counters[counterPosition];
    }

    //The counters array is encapsuled in this class so if we provide external 
    //acess to it anyone could modify it and break the purpose of the encapsulation
    //So we just exposes a copy of it :)
    public int[] ToArray()
    {
        //Now we need to fix the unupdated values in the array
        //(the values that are less than the equilibrated score)
        for (int i = 0; i < counters.Length; i++)
        {
            if (counters[i] < currentEquilibratedScore)
                counters[i] = currentEquilibratedScore;
        }

        return (int[])counters.Clone();
    }
}

Codility result