Analyze each of the corresponding algorithms according to the points as follows:

(I). Explain what value you choose for input size n. Estimate the running time (number of steps) T(n) in terms of the O(n) scale. Use the simplest and possibly the smallest valid big-Oh expressions.

(II). If it applies, give your estimates both for the worst case and best case.

(III). Document and comment each method. Describe the tasks of the methods, explain the meaning the return value if applies, show and justify your big-Oh estimate.

(IV). It is not necessary to run these methods in actual programs, but

if the task it performs is dubious, testing the method with various input in actual applications of the code may help to find its purpose and the big-Oh estimate.

NB: give your answers under comments for each method.

Exercises

A.

int find1( int[] list, int element ){

int answer = 0;

for(int k = 0; k < list.length; k++ )

if (element == list[k])

answer++;

return answer;

}//end method

Comments:

B.

public int find2(int[] arr){

int zeroCounter = find1(arr, 0);

if (zeroCounter > arr.length - 2)

return 0;

while(zeroCounter < arr.length - 2){

//see maxIndex() definition below

int max = maxIndex(arr);

arr[max] = 0;

//see display() definition below

display(arr);

zeroCounter ++;

}

return maxIndex(arr);

}//end method

//helper methods

int maxIndex(int[]arr){

int maxindex = 0;

for(int k = 0 ; k< arr.length; k++){

// note the use of absolute value

if(Math.abs(arr[maxindex]) < Math.abs(arr[k]))

maxindex = k;

}

return maxindex;

}

void display(int[]arr){

System.out.println();

for(int k = 0 ; k< arr.length; k++)

System.out.print(arr[k]+ );

System.out.println();

}

Comments