Answer:
Java.
Explanation:
public class Rectangle {
private int x;
private int y;
private int width;
private int height;
///////////////////////////////////////////////////////////
public Rectangle(int inX, inY, inWidth, inHeight) {
x = inX;
y = inY;
width = inWidth;
height = inHeight;
}
///////////////////////////////////////////////////////////
public int getX() {
return x;
}
public int getY() {
return y;
}
public int getWidth() {
return width;
}
public int getHeight() {
return height;
}
///////////////////////////////////////////////////////////
public int getArea() {
return width * height;
}
public bool isSquare() {
if (width == height) {
return true;
}
else
return false;
}
///////////////////////////////////////////////////////////
public String toString() {
return "Rectangle located at (" + x + "," + y + ")" + "with dimensions " + width + "x" + height + "and " + getArea() + "is the area.";
}
}
Answer:
Answered below
Explanation:
Index of the first element compared to the key is 5. The element itself is 55.
This index is evaluated by the addition of the index of the first element which is 0(zero) and the the index of the last element which is 10.
( Index of the last element is determined by subtracting the one from the total number of elements)
After the addition, the result is divided by 2 to get the first index from which the binary search begins.
firstIndex = 0
lastIndex = array.length - 1
midpoint = (firstIndex + lastIndex) / 2
Answer:
hahaha very funny
Explanation:
pls rate this answer a 5/5 and heart it
Hypertext Transfer Protocol
h is for hyper
the T in text is the first T
transfer is the second T
and P is for protocol
HTTP hope that helps
Answer:
Running time of algorithm is O(n).
Explanation:
n is power of 2
n =2,4,8,16,32,...................................
A is an array having n elements
B is an array of size 0 to (n/2)-1
if n=4 B then (4/2)-1 =1 So B has size 2
for(i=0;i<=(n/2)-1;++)
{
B[i]=A[2i]+A[2i+1];
}
This for loop will run n/2 times so complexity in terms of Big Oh is O(n/2) =O(n)
Running time of algorithm is O(n).
