Answer:
1. Declaration: the return type, the name of the function, and parameters (if any)
2. Definition: the body of the function (code to be executed)
Explanation:
Answer:
Table for Area codes are not missing;
See Attachment for area codes and major city I used
This program will be implemented using c++ programming language.
// Comments are used for explanatory purposes
// Program starts here
#include <iostream>
using namespace std;
int main( )
{
// Declare Variable area_code
int area_code;
// Prompt response from user
cout<<Enter your area code: ";
cin<<"area_code;
// Start switch statement
switch (area_code) {
// Major city Albany has 1 area code: 229...
case 229:
cout<<"Albany\n";
break;
// Major city Atlanta has 4 area codes: 404, 470 678 and 770
case 404:
case 470:
case 678:
case 770:
cout<<"Atlanta\n";
break;
//Major city Columbus has 2 area code:706 and 762...
case 706:
case 762:
cout<<"Columbus\n";
break;
//Major city Macon has 1 area code: 478...
case 478:
cout<<"Macon\n";
break;
//Major city Savannah has 1 area code: 912..
case 912:
cout<<"Savannah\n";
break;
default:
cout<<"Area code not recognized\n";
}
return 0;
}
// End of Program
The syntax used for the above program is; om
Answer:
The answer is "Starting address"
Explanation:
Arrays are a type of data structure that can store a fixed size successive assortment of components of a similar kind. An Array is used to store an assortment of data, yet it is regularly more valuable to consider a cluster an assortment of factors of a similar sort.
Rather than proclaiming singular factors, for example, number0, number1, ..., and number99, you declare one Array variable, for example, numbers and use numbers[0], numbers[1], and ..., numbers[99] to speak to singular factors. A particular component in a cluster is gotten to by a list.
All Arrays comprise of bordering memory areas. The most minimal address compares to the first element and the most highest address to the last element.
Answer:
When designing a cache, you have to consider this things:
If the cache has a bigger block size may have a lower delay, but when miss the miss rate will be costly. If an application has high spatial locality a bigger block size will do well, but programs with poor spatial locality will not because a miss rate will be high and seek time will be expensive.
It should be true, hopefully I’m right