Consider the following recursive algorithm. ALGORITHM Riddle(A[0..n-1]) //Input:AnarrayA[O..n -1]of real numbers if n =1 returnA[0] else temp+Riddle(A[0..n-2]) if temp ≤ A[n-1] return temp else returnA[n-1] a. What does this algorithm compute? b. Set up a recurrence relation for the algorithm's basic operation count and solve it.

Consider the following recursive algorithm. ALGORITHM Riddle(A[0..n-1]) //Input:AnarrayA[O..n -1]of real numbers if n =1 returnA[0] else temp+Riddle(A[0..n-2]) if temp ≤ A[n-1] return temp else returnA[n-1] a. What does this algorithm compute? b. Set up a recurrence relation for the algorithm's basic operation count and solve it.

Database System Concepts

7th Edition

ISBN:9780078022159

Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Chapter1: Introduction

Section: Chapter Questions

Problem 1PE

See similar textbooks

Similar questions

Consider the following recursive algorithm. Algorithm Mystery A[0..n-1]) //Input: An array A[0..n-1] of real numbers if n = 1 return A[0] else temp← Riddle(A[0..n - 2]) if temp ≤ A[n 1] return temp else return A[n - 1] a. What does this algorithm compute? b. What is its input size? c. What is its basic operation? d. Set up a recurrence relation for the algorithm's basic operation count and solve it. e. What is the efficiency class of this algorithm?
Consider the problem of computing the sum of the first n cubes: S(n) = 13 + 23 + … + n3. Design two algorithms as follows: Recursive algorithm Non-recursive algorithm Analyze the time efficiency of your two algorithms and compare which is better.
The factorial function n! has value 1, when n ≤ 1and value n * (n- 1)!, when n > 1. Write both a recursive and an iterative algorithm to Compute n!.
Consider the recursive algorithm below for computing the sum of the first n cubes: S(n) = 13 + 23 + … + n3 ALGORITHM S(n) //n is a positive integer if (n==1) return 1 else return S(n – 1) + (n*n*n); Solve the recurrence relation in your answer for the previous question. The runtime efficiency of the algorithm is? A. O(n) B. O(n2) C. O(n3) D. None of the above
Ackermann’s function is a recursive mathematical algorithm that can be used to test how well a computer performs recursion. Write a function A(m, n) that solves Ackermann’s function. Use the following logic in your function: If m = 0 then return n + 1 If n = 0 then return A(m-1, 1) Otherwise, return A(m-1, A(m, n-1)) Test your function in a driver program that displays the following values:A(0, 0) A(0, 1) A(1, 1) A(1, 2) A(1, 3) A(2, 2) A(3, 2)
ALGORITHM Y (n) // Input: n is a positive integer if n = 1 return 1 else return Y (n − 1) + n ∗ n 1. What does this algorithm compute? 2. Can the algorithm be optimised to give the same output?
*Find a non-recursive formula for f (n) : f (0) = 7, f (n) = 4f (n − 1)/9 for n ≥ 1 *Define the sequence: an = 1+ (n+3)2 for n = 1,2,3, ... recursively.
In the following recursive function, A is the input array with size n. RANDOM(n) produces a uniformly random number between 1 and n. 1: function RECALG2(A, n) if n < 5 then return A[1] 2: for i + 1 to | yn] do A[i] <- A[i] – A[[i * /n]] s– A[1] k + RANDOM(n) if k < 2n/3 then s+ s+RECALG2(A,n) 3: 4: 5: 6: 7: 8: return s (a) Determine its worst case asymptotic time complexity. (b) Using probabilistic analysis, determine its average asymptotic time complexity.
Please do not give solution in image format thanku Implement the following recursively using sudo code: Suppose an elevator which is on a floor on n. For this elevator to go from the nth floor to the base(ground) floor, it should go to every floor under the nth floor. Let's consider an elevator on the 4th floor. This elevator 1st comes on the third(3rd) floor. 4th-> 3rd then 3rd-> 2nd then 2->1 and next 1->0(ground floor) The recursive equation defined is F(n)=1+F(n-1)
The following recursive procedure computes the n-th Fibonacci number. Fib(n) 1 ifn<= 1 2 return n 3 else return Fib(n - 1) + Fib(n - 2) Use memoization technique to develop an efficient version of Fib(n). Give your solution in pseudocode, similar to what is given above.
A recursive algorithm has been developed as shown below: Input: List A = (a₁,..., an) such that N > 1 Output: value x foo(A) if length(A) == 1 return a₁ A' = (a₁,..., aN-1) q = foo(A') if (q> an) else return q return an State what problem this algorithm solves and write down the two recurrence equations that characterise this recursive algorithm.
Part 2 of 2 - Consider the recursive algorithm below for computing the sum of the first n cubes: S(n) = 13 + 23 + + n3 ALGORITHM S (n) //n is a positive integer if (n=31) return 1 else return S(n 1) + (n*n*n);