QUICKSORT(A, p, r)if p < rthen q + PARTITION(A, p, r)QUICKSORT(A, p, q - 1)QUICKSORT(A, q + 1, r)where the PARTITION procedure is as follows:PARTITION (A, p, r)x - A[r]i-p-1for j - p to r - 1do if A[j] ≤ xthen i + i + 1exchange A[i]exchange A[i+1] → A[r]return i + 1A[j]Draw the flowchart of the above algorithm.• Draw the corresponding graph and label the nodes as n1, n2, ... and edges as e1,e2, ...• Calculate the cyclomatic complexity of the above algorithm

QUICKSORT(A, p, r) if p < r then q - PARTITION(A, p, r) QUICKSORT(A, p. q - 1) QUICKSORT(A, q + 1, r) where the PARTITION procedure is as follows: PARTITION (A, p, r) x - A[r] i-p-1 for j - p to r - 1 do if A[j] ≤ x then i + i + 1 exchange A[i] → A[j] exchange A[i+1] → A[r] return i + 1 Draw the flowchart of the above algorithm. • Draw the corresponding graph and label the nodes as n1, n2, ... and edges as e1,e2, ... • Calculate the cyclomatic complexity of the above algorithm

QUICKSORT(A, p, r) if p < r then q - PARTITION(A, p, r) QUICKSORT(A, p. q - 1) QUICKSORT(A, q + 1, r) where the PARTITION procedure is as follows: PARTITION (A, p, r) x - A[r] i-p-1 for j - p to r - 1 do if A[j] ≤ x then i + i + 1 exchange A[i] → A[j] exchange A[i+1] → A[r] return i + 1 Draw the flowchart of the above algorithm. • Draw the corresponding graph and label the nodes as n1, n2, ... and edges as e1,e2, ... • Calculate the cyclomatic complexity of the above algorithm

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

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The capacity of a cut is defined as the sum of capacities of nodes that composes the cut. O True O False
Cjupyter E4 Last Checkpoint: Last Wednesday at 7:17 PM (autosaved) Logout File Edit View Insert Cll Kernel Widgets Help Trusted | Python 3 O + Run Markdown Exercise 4: Using Proofs in Algorithms Problem Statement Prove that the following algorithm is correct: In [1]: def insertSort (A): The Algorithm sorts the elements in the list A Input constraints: A is not empty for i in range(1,len(A)): j - i-1 while A[j]>A[j+1] and j>=0: A[j],A[j+1] - A[j+1],A[j] j -- 1 In [3]: A = [3,1,11,9,10,2] insertSort (A) print (A) [1, 2, 3, 9, 1ө, 11]
SML!!!!! use let expressions and pattern matching Define a function is_sorted: (’a * ’a -> bool) -> ’a list -> bool to test whether a list is sorted in a specific order. For example, is_sorted (op >) [4,3,2,1] returns true while is_sorted (op >) [4,3,1,2] returns false. MUST USE SML!!! make sure!!!!!!!!!!!!!!!!! (op >) is included DO NOT take incorect python answers only in sml.
3. Consider the following sorting algorithm EASYSORT: Algorithm EASYSORT(A, n) if (n > 1) then for i - n downto 2 do for j+1 to i – 1 do if (A[j+ 1] < A[j]) then exchange A[j + 1] and A[j] (a) Draw the decision tree for EASYSORT with n = 3. You may assume that all elements are distinct.
Use partition algorithm I Need correct figure only upvote otherwise more downvotes I will give u
5. Consider the following Algorithms and explain (a) Merge Sort uses what sort of optimisation: greedy, backtracking or divide and conquer? MergeSort (arr[), 1, r) If r > 1 1. Find the middle point to divide the array into two halves: middle m = 1+ (r-1)/2 2. Call mergeSort for first half: Call mergeSort(arr, 1, m) 3. Call mergeSort for second half: Call mergeSort(arr, m+1, r) 4. Merge the two halves sorted in step 2 and 3: Call merge (arr, 1, m, r) (b) Find Shortest Path to Node To search for shortest path you can use Breadth First or Depth First Search. What is the optimum approach? Traverse the graph breadthwise as follows: a. First move horizontally and visit all the nodes of the current layer b. Move to the next layer Traverse the graph depthwise as follows: a. Create a recursive function that takes the index of the node and a visited array. b. Mark the current node as visited and print the node. c. Traversę all the adjacent and unmarked nodes and call the recursive function with…
Suppose we wish to sort the following values: 84, 22, 19, 11, 60, 68, 31, 29, 58, 23, 45, 93, 48, 31, 7. Assume that: we have three pages of memory for sorting; we will use an external sorting algorithm with a 2-way merge; a page only holds two values. We do not use double buffering and we use quick sort in pass 0 to produce the initial runs. For each sorting pass, show the contents of all temporary files except that you should fully utilize the buffers by sorting every 3 pages into a run in pass 0. Could you show step by step detailed explaination for this?
use the partition function given when writing quicksort algorithm
All parts of Q11 please.
Implement the following algorithms in Java:The pseudocode for QUICKSORT introduced in (slide 14), includingprocedure PARTITION implementing right-most element pivot selection (slide 13). Slide 13:PARTITION(A,p,r) x := A[r] i := p – 1 for j = p to r - 1 if A[j]  x i := i + 1 SWAP(A[i],A[j]) SWAP(A[i+1],A[r]) return i + 1 Slide 14:QUICKSORT(A,p,r) if p < r q := PARTITION(A,p,r) QUICKSORT(A,p,q-1) QUICKSORT(A,q+1,r)
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