Introduction to Java Programming and Data Structures, Comprehensive Version (11th Edition)
11th Edition
ISBN: 9780134670942
Author: Y. Daniel Liang
Publisher: PEARSON
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Textbook Question
Chapter 22.3, Problem 22.3.2CP
How many stars are displayed in the following code if n is 10? How many if n is 20? Use the Big O notation to estimate the time complexity.
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Chapter 22 Solutions
Introduction to Java Programming and Data Structures, Comprehensive Version (11th Edition)
Ch. 22.2 - Prob. 22.2.1CPCh. 22.2 - What is the order of each of the following...Ch. 22.3 - Count the number of iterations in the following...Ch. 22.3 - How many stars are displayed in the following code...Ch. 22.3 - Prob. 22.3.3CPCh. 22.3 - Prob. 22.3.4CPCh. 22.3 - Example 7 in Section 22.3 assumes n = 2k. Revise...Ch. 22.4 - Prob. 22.4.1CPCh. 22.4 - Prob. 22.4.2CPCh. 22.4 - Prob. 22.4.3CP
Ch. 22.4 - Prob. 22.4.4CPCh. 22.4 - Prob. 22.4.5CPCh. 22.4 - Prob. 22.4.6CPCh. 22.5 - Prob. 22.5.1CPCh. 22.5 - Why is the recursive Fibonacci algorithm...Ch. 22.6 - Prob. 22.6.1CPCh. 22.7 - Prob. 22.7.1CPCh. 22.7 - Prob. 22.7.2CPCh. 22.8 - Prob. 22.8.1CPCh. 22.8 - What is the difference between divide-and-conquer...Ch. 22.8 - Prob. 22.8.3CPCh. 22.9 - Prob. 22.9.1CPCh. 22.9 - Prob. 22.9.2CPCh. 22.10 - Prob. 22.10.1CPCh. 22.10 - Prob. 22.10.2CPCh. 22.10 - Prob. 22.10.3CPCh. 22 - Program to display maximum consecutive...Ch. 22 - (Maximum increasingly ordered subsequence) Write a...Ch. 22 - (Pattern matching) Write an 0(n) time program that...Ch. 22 - (Pattern matching) Write a program that prompts...Ch. 22 - (Same-number subsequence) Write an O(n) time...Ch. 22 - (Execution time for GCD) Write a program that...Ch. 22 - (Geometry: gift-wrapping algorithm for finding a...Ch. 22 - (Geometry: Grahams algorithm for finding a convex...Ch. 22 - Prob. 22.13PECh. 22 - (Execution time for prime numbers) Write a program...Ch. 22 - (Geometry: noncrossed polygon) Write a program...Ch. 22 - (Linear search animation) Write a program that...Ch. 22 - (Binary search animation) Write a program that...Ch. 22 - (Find the smallest number) Write a method that...Ch. 22 - (Game: Sudoku) Revise Programming Exercise 22.21...Ch. 22 - (Bin packing with smallest object first) The bin...Ch. 22 - Prob. 22.27PE
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- q11) Find the time complexity for the program code and represent it in Big O notation. int p=3, q=5, r; for(int i=0;i<n;i++) { r= p * q * i; q++; } cout<<r; a. 1 b. O(log n) c. O( n ) d. O(n2)arrow_forwardWhat is the growth rate of the following algorithm? y = 1; for (i=1; i<=n;i++) { for (j = 1; j<=n;j++) { x = A[i] + A[j]; x = x * y; } y = y + x; }arrow_forwardT. 1011: 100110 x 1011 100110 (10011011) 100110 (10011012) 000000 (10011004, but we skip this step in the algorithm) (10011018) 100110 110100010.arrow_forward
- What one of the following is false? The complexity of time requires more CPU cycles. Less memory is needed because of space's complexity. Time complexity is calculated using the total number of operations. The worst situation for an algorithm is when there are too many operations.arrow_forwardWhat is the growth rate of the following algorithm? Is the worst case different than the average case? Why? y = 1; for (i=1; i<=n; i++) { for (j=1; j<=n; j++) { x = A[i] + A[j]; x = x * y; } y = y + x; }arrow_forwardWhat is the big oh O , (the complexity) of the algorithm?.arrow_forward
- Looking at the following algorithm, please give an analysis of it in terms of time complexity using mathematics and put it in big O notation! Algorithm A: k := 0 For i = 1 to n: For j = (i + 1) to n: k = k + j + i Return karrow_forward*n = A.length;int x;for (int i = 0; i <n; i ++) { x = 1; while (x <n) { x = x + 2; }} x = x / 2;while (x> = 0) { System.out.println (A [0]); x--;} This algorithm has a Grand O complexity of ... (select all the correct answers): O(n) O (n log2 n) none of the above O (log2n)arrow_forwardi = 0, j = 0 For(a = 0; a*a < n; a++){ For(b = 0; b < n; b *= 2){ For(c = 0; c*c < n; c++){ i += i j = j*2 } } } What is the time complexity for the code? (a) O(n−−√∗n∗n) (b) O(n−−√∗logn∗n−−√) (c) O(n∗logn) (d) O(n2.5) (e) O(n)arrow_forward
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