2) How much time does the following “algorithm” require as a function of n?
l =0
for i = 1 to n do
for j = 1 to n2 do
for k = 1 to n3 do
l = l + 1
2) How much time does the following “algorithm” require as a function of n? l...
3) How much time does the following “algorithm” require as a function of n? l=0 for i=1 to n do for j=1 to i do for k=j to n do l = l + 1
How much time does the following "algorithm" require as a function Problem 4.1. of n? for i 1 to n do for j 1 to n do for k 1 to n3 do Express your answer in 6 notation in the simplest possible form. You may consider that each individual instruction (including loop control) is elementary
Perform the following to the algorithm below: - - Express T(n) as a function of n Find a best approximation for the Big O function for T(n) Perform a time complexity analysis Define the basic operation of the algorithm Correctness Efficiency - - Procedure maxMin (n, A, I, h) integer h, I, A (1:n), n integer j j-2 IA (1) hS (1) while (i <=n) do if (Ali) < 1) then TEA (0) if(Ali) >h) then h A() j+į+1 repeat...
1. (10 points) Write an efficient iterative (i.e., loop-based) function Fibonnaci(n) that returns the nth Fibonnaci number. By definition Fibonnaci(0) is 1, Fibonnaci(1) is 1, Fibonnaci(2) is 2, Fibonnaci(3) is 3, Fibonnaci(4) is 5, and so on. Your function may only use a constant amount of memory (i.e. no auxiliary array). Argue that the running time of the function is Θ(n), i.e. the function is linear in n. 2. (10 points) Order the following functions by growth rate: N, \N,...
Consider the following algorithm. ALGORITHM Enigma(A[0.n - 1]) //Input: An array A[0.n - 1] of integer numbers for i leftarrow 0 to n - 2 do for j leftarrow i +1 to n - 1 do if A[i] = = A[j] return false return true a) What does this algorithm do? b) Compute the running time of this algorithm.
Analyze the running time of the following algorithms asymptotically. (a) Algorithm for-loop(n): P = 1 for i = 1 to 5n^2 do p = p times i return p (b) Algorithm for-loop(n): s = 0 for i = 1 to n do for j = I to n do s = s + i return s (c) Algorithm WhileLoop(n): x = 0; j = 2; while (j = n){x = x+ 1; j =j times 2;}
1 question) Arrange the following in the order of their growth rates, from least to greatest: (5 pts) n3 n2 nn lg n n! n lg n 2n n 2 question)Show that 3n3 + n2 is big-Oh of n3. You can use either the definition of big-Oh (formal) or the limit approach. Show your work! (5 pts.) 3 question)Show that 6n2 + 20n is big-Oh of n3, but not big-Omega of n3. You can use either the definition of big-Omega...
Question 2 Consider the following algorithm Fun that takes array A and key Kas Fun(AO,...,n - 1], K) count = 0 for i = 0 ton - 1 do for j = i +1 to n - 1 do if A[i] + A[j] == K then count = count +1 end if end for end for return count What is the best case time complexity of the above algorithm?! (log(n)) O(1) (n) (na) Previous o H H 9
a) Prove that running time T(n)=n3+30n+1 is O(n3) [1 mark] b) Prove that running time T(n)=(n+30)(n+5) is O(n2) [1 mark] c) Count the number of primitive operation of algorithm unique1 on page 174 of textbook, give a big-Oh of this algorithm and prove it. [2 mark] d) Order the following function by asymptotic growth rate [2 mark] a. 4nlogn+2n b. 210 c. 3n+100logn d. n2+10n e. n3 f. nlogn
(V). Given the following algorithm, answer relevant questions. Algorithm 1 An algorithm 1: procedure WHATISTHIS(21,22,...,n: a list of n integers) for i = 2 to n do c= j=i-1 while (j > 0) do if ra; then break end if 4j+1 = a; j= j-1 end while j+1 = 1 end for 14: return 0.02. 1, 15: end procedure Answer the following questions: (1) Run the algorithm with input (41, 02, 03, 04) = (3, 0, 1,6). Record the values...