Database System Concepts
7th Edition
ISBN: 9780078022159
Author: Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher: McGraw-Hill Education
expand_more
expand_more
format_list_bulleted
Question
Records with equal keys are kept in the same order via stable sorting algorithms (i.e. values).
In other words, a sorting technique is stable if R occurs before S in the original list and R appears before S in the sorted list whenever R and S have the same key.
Is the counting-sort algorithm stable?
Expert Solution
This question has been solved!
Explore an expertly crafted, step-by-step solution for a thorough understanding of key concepts.
Step by stepSolved in 4 steps
Knowledge Booster
Learn more about
Need a deep-dive on the concept behind this application? Look no further. Learn more about this topic, computer-science and related others by exploring similar questions and additional content below.Similar questions
- Q1Apply selection sort for the following list to sort it in ascending order. Record your answer for the first two passes. 80 Pass 1 29 Pass 2 73 43 97 How many comparisons and exchanges are done in each pass of the selection sort algorithm? Comparisons Passes Exchanges 52 Original Pass 1 Pass 2arrow_forwardQuestion 6: Professor Holmes has come up with a new sorting algorithm. He calls it Trinary Sort and "claims" that it is asymptotically faster than Merge Sort, despite the fact both the algorithms operate using similar logic. But, unlike Merge Sort, Trinary Sort splits the input array into (roughly) 3 equal parts at each step of the recursion as long as the array is splittable (i.e., has at least 3 elements). Trinary Sort's merge subroutine, similar in principle to the one used by Merge Sort, takes 3 sorted subarrays and merges them to produce a single sorted array. Given all of this, answer the following questions. (a) In Merge Sort, the merge subroutine makes n-1 comparisons to merge 2 arrays of size n/2, which takes (n) time. How many comparisons will the merge subroutine of Trinary Sort make to merge 3 arrays of size n/3? What would be the (...) bound on the running time for this subroutine? (b) What is the (...) bound on the running time of the Trinary Sort algorithm? Come up with…arrow_forwardPls answer correctly and show all workarrow_forward
- The Big O of the linear search is O(n) and of the binary search is O(log n). What key aspectof both the binary search (Chapter 6) and the merge sort accounts for the logarithmic portion oftheir respective Big Os?arrow_forwardTrace counting sort on the following list L of unordered keys which lie withinthe range [10, 18].L[1:10]: 16 11 18 13 11 12 15 15 18 16arrow_forwardPlease explain Q#Do the time complexities of a singly linked list differ from the time complexities of the operations (update, insert, lookup, delete) of a doubly-linked list? Group of answer choices a. Yes, the Big-O complexities are different for some of the operations. Adding the additional pointer to the previous node in the doubly linked list makes half of the operations slower. b. No, the Big-O complexities do not differ. While a Doubly linked list uses an additional pointer of memory, it does not in fact modify the Big-O run-time. c. Yes, the Big-O complexities are different for all of the operations. Adding the additional pointer to the previous node in the doubly linked list makes all operations slower.arrow_forward
- 3 illustrates the counting sort algorithm. For simplicity ofimplementation and understanding, the range (a, b) within which the unordered setof keys lie is assumed to be within (0, k).arrow_forwardMerge Sort Algorithm to remove duplicates from a text list. Show Complexity Analysis. Example, [Mike,Keya,Mike,John] -> [Mike,Keya,John] The order doesn't matter.arrow_forwardTrace the execution of Bubble-sort on the list: 30, 7, 21, 42, 57, 90, 3, 11arrow_forward
- Trace counting sort on the following list L of unordered keys which lie withinthe range [10, 18].L[1:10]: 16 11 18 13 11 12 15 15 18 16arrow_forward2. Given the resulting sorted list, trace the execution for a binary search, searching for the number 97. Note: the index of midpoints is (i+j)/2, where i and j are starting and ending indices in a step. 2 6 11 25 35 56 80 88 97 99arrow_forward
arrow_back_ios
arrow_forward_ios
Recommended textbooks for you
- Database System ConceptsComputer ScienceISBN:9780078022159Author:Abraham Silberschatz Professor, Henry F. Korth, S. SudarshanPublisher:McGraw-Hill EducationStarting Out with Python (4th Edition)Computer ScienceISBN:9780134444321Author:Tony GaddisPublisher:PEARSONDigital Fundamentals (11th Edition)Computer ScienceISBN:9780132737968Author:Thomas L. FloydPublisher:PEARSON
- C How to Program (8th Edition)Computer ScienceISBN:9780133976892Author:Paul J. Deitel, Harvey DeitelPublisher:PEARSONDatabase Systems: Design, Implementation, & Manag...Computer ScienceISBN:9781337627900Author:Carlos Coronel, Steven MorrisPublisher:Cengage LearningProgrammable Logic ControllersComputer ScienceISBN:9780073373843Author:Frank D. PetruzellaPublisher:McGraw-Hill Education
Database System Concepts
Computer Science
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:McGraw-Hill Education
Starting Out with Python (4th Edition)
Computer Science
ISBN:9780134444321
Author:Tony Gaddis
Publisher:PEARSON
Digital Fundamentals (11th Edition)
Computer Science
ISBN:9780132737968
Author:Thomas L. Floyd
Publisher:PEARSON
C How to Program (8th Edition)
Computer Science
ISBN:9780133976892
Author:Paul J. Deitel, Harvey Deitel
Publisher:PEARSON
Database Systems: Design, Implementation, & Manag...
Computer Science
ISBN:9781337627900
Author:Carlos Coronel, Steven Morris
Publisher:Cengage Learning
Programmable Logic Controllers
Computer Science
ISBN:9780073373843
Author:Frank D. Petruzella
Publisher:McGraw-Hill Education