n
log n
1

2. (TCO 4) Algorithms can be described using _____. (Points : 3)
pseudocode
assignment and arithmetic operations
loops and decision statements
All of the above

3. (TCO 4) The running time of an algorithm is _____. (Points : 3)
the time, in milliseconds, it takes to complete its execution
the running time of its implementation
the maximum number of basic operations executed by the algorithm (over all inputs of size N)
the number of steps given in its description

4. (TCO 4) The running time of an algorithm to find the maximum of a collection of n
numbers stored in an array is _____. (Points : 3)
O(n2)
O(n
log n)
O(n)
O(1)

5. (TCO 5) Consider the recursive function below.

int RecFunction(int n)
{
if (n==0) return 0;
else return RecFunction(n-1) + n;
}

Which does this code do? (Points : 3)
Returns n
+ (n – 1)
Returns the sum of numbers 0 to n
Returns the factorial of a number n
Returns the nth Fibonacci number

6. (TCO 5) Consider the function below.

long x(int n)
{
if (n == 1) return 1;
else return n*x(n-1);
}

Which will be displayed by the following cout statement?

cout << x(5) << endl; (Points : 3) 120 25 6 1 7. (TCO 5) In the worst case, bubble sort uses _____ steps. (Points : 3) O(1) O(n2) O(n log n) O(2n) 8. (TCO 5) A method that performs very well in practice, even though its worst-case running time is quadratic, is _____. (Points : 3) bubble sort insertion sort mergesort quicksort