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Question

Consider an array $A$ of integers of size $n$. The indices of $A$ run from 1 to $n$. An algorithm is to be designed to check whether $A$ satisfies the condition given below.

$\forall i,j \in \{1, \dots, n-1\}$ such that $i > j$, $(A[i + 1] - A[i]) > (A[j + 1] - A[j])$

Which one of the following gives the worst case time complexity of the fastest algorithm that can be designed for the problem?

The correct answer is
$\Theta(n)$

Algorithm Condition Analysis

The problem requires checking a specific condition on an array $A$ of size $n$. The condition is stated as:

$ \forall i,j \in \{1, \dots, n-1\} \text{ such that } i > j, \quad (A[i + 1] - A[i]) > (A[j + 1] - A[j]) $

Let's define the difference between adjacent elements as $D[k] = A[k+1] - A[k]$ for $k \in \{1, \dots, n-1\}$.

The condition simplifies to ensuring that the sequence of differences, $D[1], D[2], \dots, D[n-1]$, is strictly increasing. That is:

$ D[1] < D[2] < \dots < D[n-1] $

Fastest Algorithm Verification

To verify this condition, the fastest algorithm must perform the following steps:

  • Compute all adjacent differences $D[k] = A[k+1] - A[k]$ for $k$ from 1 to $n-1$. This requires accessing elements $A[1]$ through $A[n]$.
  • Check if these computed differences are strictly increasing, i.e., $D[k] < D[k+1]$ for all $k$ from 1 to $n-2$.

Time Complexity Calculation

The process involves:

  • Computing Differences: Calculating $n-1$ differences requires $n-1$ subtraction operations. Accessing the necessary array elements ($A[1]$ to $A[n]$) takes time proportional to $n$. This step is $\Theta(n)$.
  • Checking Order: Comparing adjacent differences requires $n-2$ comparison operations. This step is also $\Theta(n)$.

The total time complexity is the sum of the time taken for these steps: $\Theta(n) + \Theta(n) = \Theta(n)$.

Since the algorithm must inspect all adjacent differences to guarantee the condition holds, it needs to access a significant portion of the array, establishing $\Omega(n)$ as a lower bound. As we have an algorithm that achieves $\Theta(n)$, this is the tightest bound for the fastest algorithm.

Conclusion

The worst-case time complexity of the fastest algorithm to check the given array condition is $\Theta(n)$.

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Important Questions from Array

  1. Which of the following expression will delete the entire array pointed to by q?

  2. Consider the following C program segment.

    #include <stdio.h>

    int main()
    {
      char s1[7] = "1234";
        char *p;

        p = s1 + 2;
        *p = '0';

        printf("%s", s1);

        return 0;
    }

    What will be printed by the program?
  3. #include <stdio.h>
    
    void foo(int *p, int x){
        *p = x;
    }
    
    int main(){
        int *z;
        int a = 20, b = 25;
        z = &a;
        foo(z, b);
        printf("%d", a);
        return 0;
    }
    
    The output of the given C program is __________. (Answer in integer)
  4. What is the output the given C language code snippet? 

    #include<stdio.h>

     int main()

    {

     int x[] = {10,20,30}; 

    int *p = x; 

    p++; 

    printf("%d",*p); 

    return 0; 

    }

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