Big-O Exercises

last updated 1/7/08

These exercises are borrowed from Headington/Riley, Data Abstraction and Structures Using C++, DC Heath, 1994.

Below are pairs of cost/time functions. Determine the best big-Oh and which of the pair dominates or neither.

Cost Function Domination and big-Oh Determination
  Functions Domination:
T1 or T2 or neither
big-Oh
a. T1(X) = 2*X2
T2(X) = 2*X
   
b. T1(X) = 5*X2
T2(X) = 2*X3
   
c. T1(Y) = 55*Y15+3*Y4+7500
T2(Y) = Y16+2
   
d. T1(Z) = (Z+3)(Z+9)
T2(Z) = 250*Z
   
e. T1(Z) = (Z+7)(Z+5)
T2(Z) = 2*Z3
   
f. T1(N) = 37*N2
T2(N) = N log N
   
g. T1(N) = 37*N2
T2(N) = N2 log N
   
h. T1(N) = log2N
T2(N) = log3N
   
i. T1(N) = 84
T2(N) = log9N
   
j. T1(X) = (3*X+2)/X
T2(X) = 766*X
   
k. T1(X) = (X4+X2-17)/X3
T2(X) = X2
   
l. T1(W) = W9
T2(W) = 9W
   
m. T1(W) = W!
T2(W) = 67W
   
n. T1(V) = VV
T2(V) = 25V
   
o. T1(N) = 55*N3+77*N2+99
T2(N) = 2N+N2
   
p. T1(N) = 3N+N2
T2(N) = 2N*N2
   
q. T1(N) = (N log N)/(2+N)
T2(N) = log N + 46*N
   

Rank the following big-O measures from least to greatest. Name them (constant, linear, quadratic, cubic, logarithmic, polynomial, factorial and exponential)

Big-O Ranks and Names
  Rank Name
O(N)    
O(N!)    
O(4N)    
O(log4N)    
O(log3N)    
O(N2)    
O(1)    
O(N log2 N)    
O(N2 log2 N)    
O(N3)