SlideShare ist ein Scribd-Unternehmen logo
1 von 33
Insertion Sort &
        Shellsort
By: Andy Le
CS146 – Dr. Sin Min Lee
Spring 2004
Outline
 Importance of Sorting
 Insertion Sort
     Explanation
     Runtime
     Advantage and Disadvantage
     Walk through example
 Shell Sort
     History
     Explanation
     Runtime
     Advantage and Disadvantage
     Walk through example
Why we do sorting?
 Commonly encountered programming task in
  computing.
 Examples of sorting:
   List containing exam scores sorted from Lowest to
    Highest or from Highest to Lowest
   List containing words that were misspelled and be
    listed in alphabetical order.
   List of student records and sorted by student
    number or alphabetically by first or last name.
Why we do sorting?

 Searching for an element in an array will
  be more efficient. (example: looking up
  for information like phone number).
 It’s always nice to see data in a sorted
  display. (example: spreadsheet or
  database application).
 Computers sort things much faster.
History of Sorting

 Sorting is one of the most important
  operations performed by computers. In
  the days of magnetic tape storage before
  modern databases, database updating
  was done by sorting transactions and
  merging them with a master file.
History of Sorting

 It's still important for presentation of data
  extracted from databases: most people
  prefer to get reports sorted into some
  relevant order before flipping through
  pages of data!
Insertion Sort
 Insertion sort keeps making the left side of the
  array sorted until the whole array is sorted. It
  sorts the values seen far away and repeatedly
  inserts unseen values in the array into the left
  sorted array.
 It is the simplest of all sorting algorithms.
 Although it has the same complexity as Bubble
  Sort, the insertion sort is a little over twice as
  efficient as the bubble sort.
Insertion Sort

 Real life example:
   An example of an insertion sort occurs in
    everyday life while playing cards. To sort the
    cards in your hand you extract a card, shift
    the remaining cards, and then insert the
    extracted card in the correct place. This
    process is repeated until all the cards are in
    the correct sequence.
Insertion Sort runtimes

 Best case: O(n). It occurs when the data
  is in sorted order. After making one pass
  through the data and making no
  insertions, insertion sort exits.
 Average case: θ(n^2) since there is a
  wide variation with the running time.
 Worst case: O(n^2) if the numbers were
  sorted in reverse order.
Empirical Analysis of Insertion Sort




   The graph demonstrates the n^2 complexity of the insertion sort.

Source: http://linux.wku.edu/~lamonml/algor/sort/insertion.html
Insertion Sort

 The insertion sort is a good choice for
  sorting lists of a few thousand items or
  less.
Insertion Sort

 The insertion sort shouldn't be used for
  sorting lists larger than a couple
  thousand items or repetitive sorting of
  lists larger than a couple hundred items.
Insertion Sort

 This algorithm is much simpler than the
  shell sort, with only a small trade-off in
  efficiency. At the same time, the insertion
  sort is over twice as fast as the bubble
  sort.
Advantage of Insertion Sort

 The advantage of Insertion Sort is that it
  is relatively simple and easy to
  implement.
Disadvantage of Insertion Sort

 The disadvantage of Insertion Sort is that
  it is not efficient to operate with a large
  list or input size.
Insertion Sort Example

      Sort: 34 8 64 51 32 21
 34 8 64 51 32 21
  The algorithm sees that 8 is smaller than 34
   so it swaps.
 8 34 64 51 32 21
  51 is smaller than 64, so they swap.
 8 34 51 64 32 21
Insertion Sort Example
      Sort: 34 8 64 51 32 21
 8 34 51 64 32 21 (from previous slide)
   The algorithm sees 32 as another smaller
    number and moves it to its appropriate
    location between 8 and 34.
 8 32 34 51 64 21
   The algorithm sees 21 as another smaller
    number and moves into between 8 and 32.
 Final sorted numbers:
 8 21 32 34 51 64
Shellsort
 Founded by Donald Shell and named the
  sorting algorithm after himself in 1959.
 1st algorithm to break the quadratic time barrier
  but few years later, a sub quadratic time bound
  was proven
 Shellsort works by comparing elements that
  are distant rather than adjacent elements in an
  array or list where adjacent elements are
  compared.
Shellsort

 Shellsort uses a sequence h1, h2, …, ht
  called the increment sequence. Any
  increment sequence is fine as long as h 1
  = 1 and some other choices are better
  than others.
Shellsort

 Shellsort makes multiple passes through
  a list and sorts a number of equally sized
  sets using the insertion sort.
Shellsort

 Shellsort improves on the efficiency of
  insertion sort by quickly shifting values to
  their destination.
Shellsort

 Shellsort is also known as diminishing
  increment sort.
 The distance between comparisons
  decreases as the sorting algorithm runs
  until the last phase in which adjacent
  elements are compared
Shellsort

 After each phase and some increment
  hk, for every i, we have a[ i ] ≤ a [ i + hk ]
  all elements spaced hk apart are sorted.
 The file is said to be hk – sorted.
Empirical Analysis of Shellsort




 Source: http://linux.wku.edu/~lamonml/algor/sort/shell.html
Empirical Analysis of Shellsort
        (Advantage)
 Advantage of Shellsort is that its only
  efficient for medium size lists. For bigger
  lists, the algorithm is not the best choice.
  Fastest of all O(N^2) sorting algorithms.
 5 times faster than the bubble sort and a
  little over twice as fast as the insertion
  sort, its closest competitor.
Empirical Analysis of Shellsort
       (Disadvantage)
 Disadvantage of Shellsort is that it is a complex
  algorithm and its not nearly as efficient as the
  merge, heap, and quick sorts.
 The shell sort is still significantly slower than
  the merge, heap, and quick sorts, but its
  relatively simple algorithm makes it a good
  choice for sorting lists of less than 5000 items
  unless speed important. It's also an excellent
  choice for repetitive sorting of smaller lists.
Shellsort Best Case

 Best Case: The best case in the shell
  sort is when the array is already sorted in
  the right order. The number of
  comparisons is less.
Shellsort Worst Case

 The running time of Shellsort depends on
  the choice of increment sequence.
 The problem with Shell’s increments is
  that pairs of increments are not
  necessarily relatively prime and smaller
  increments can have little effect.
Shellsort Examples
      Sort: 18 32 12 5 38 33 16 2
        8 Numbers to be sorted, Shell’s increment will be floor(n/2)
         * floor(8/2)  floor(4) = 4

         increment 4: 1         2        3         4      (visualize underlining)

                          18 32 12 5 38 33 16            2

Step 1) Only look at 18 and 38 and sort in order ;
18 and 38 stays at its current position because they are in order.
Step 2) Only look at 32 and 33 and sort in order ;
32 and 33 stays at its current position because they are in order.
Step 3) Only look at 12 and 16 and sort in order ;
12 and 16 stays at its current position because they are in order.
Step 4) Only look at 5 and 2 and sort in order ;
2 and 5 need to be switched to be in order.
Shellsort Examples (con’t)
      Sort: 18 32 12 5 38 33 16 2
Resulting numbers after increment 4 pass:
      18 32 12 2          38 33 16 5
* floor(4/2)  floor(2) = 2
 increment 2:    1   2

            18       32        12       2        38        33       16          5
  Step 1) Look at 18, 12, 38, 16 and sort them in their appropriate location:

            12       38        16       2        18        33       38          5
  Step 2) Look at 32, 2, 33, 5 and sort them in their appropriate location:
            12       2         16       5        18        32       38          33
Shellsort Examples (con’t)
         Sort: 18 32 12 5 38 33 16 2
* floor(2/2)  floor(1) = 1
 increment 1: 1
         12       2           16   5    18    32      38      33

         2        5           12   16   18    32      33     38


   The last increment or phase of Shellsort is basically an Insertion
   Sort algorithm.
Additional Online References

 Spark Notes (From Barnes & Noble):
   http://www.sparknotes.com/cs/
The End

Weitere ähnliche Inhalte

Was ist angesagt?

Was ist angesagt? (20)

Binary search tree(bst)
Binary search tree(bst)Binary search tree(bst)
Binary search tree(bst)
 
Selection sort
Selection sortSelection sort
Selection sort
 
Data Structures - Lecture 9 [Stack & Queue using Linked List]
 Data Structures - Lecture 9 [Stack & Queue using Linked List] Data Structures - Lecture 9 [Stack & Queue using Linked List]
Data Structures - Lecture 9 [Stack & Queue using Linked List]
 
Queue data structure
Queue data structureQueue data structure
Queue data structure
 
Insertion Sorting
Insertion SortingInsertion Sorting
Insertion Sorting
 
single linked list
single linked listsingle linked list
single linked list
 
Merge sort algorithm
Merge sort algorithmMerge sort algorithm
Merge sort algorithm
 
Searching techniques in Data Structure And Algorithm
Searching techniques in Data Structure And AlgorithmSearching techniques in Data Structure And Algorithm
Searching techniques in Data Structure And Algorithm
 
Binary Search - Design & Analysis of Algorithms
Binary Search - Design & Analysis of AlgorithmsBinary Search - Design & Analysis of Algorithms
Binary Search - Design & Analysis of Algorithms
 
Linked lists
Linked listsLinked lists
Linked lists
 
Breadth First Search & Depth First Search
Breadth First Search & Depth First SearchBreadth First Search & Depth First Search
Breadth First Search & Depth First Search
 
Data structure , stack , queue
Data structure , stack , queueData structure , stack , queue
Data structure , stack , queue
 
linked list in data structure
linked list in data structure linked list in data structure
linked list in data structure
 
Graph traversals in Data Structures
Graph traversals in Data StructuresGraph traversals in Data Structures
Graph traversals in Data Structures
 
Priority Queue in Data Structure
Priority Queue in Data StructurePriority Queue in Data Structure
Priority Queue in Data Structure
 
Binary Search
Binary SearchBinary Search
Binary Search
 
Shell sort
Shell sortShell sort
Shell sort
 
Abstract data types (adt) intro to data structure part 2
Abstract data types (adt)   intro to data structure part 2Abstract data types (adt)   intro to data structure part 2
Abstract data types (adt) intro to data structure part 2
 
Arrays
ArraysArrays
Arrays
 
stack and queue array implementation in java.
stack and queue array implementation in java.stack and queue array implementation in java.
stack and queue array implementation in java.
 

Andere mochten auch (7)

Insertion sort
Insertion sortInsertion sort
Insertion sort
 
Insertion sort
Insertion sortInsertion sort
Insertion sort
 
Insertion Sort Algorithm
Insertion Sort AlgorithmInsertion Sort Algorithm
Insertion Sort Algorithm
 
Selection Sort - Vipin Ramola
Selection Sort - Vipin RamolaSelection Sort - Vipin Ramola
Selection Sort - Vipin Ramola
 
Insertion Sort
Insertion SortInsertion Sort
Insertion Sort
 
Insertion sort
Insertion sortInsertion sort
Insertion sort
 
Advanced Sorting Algorithms
Advanced Sorting AlgorithmsAdvanced Sorting Algorithms
Advanced Sorting Algorithms
 

Ähnlich wie Sorting Techniques

Is sort andy-le
Is sort andy-leIs sort andy-le
Is sort andy-le
Sumedha
 
Shell sort in Data Structure Using C
Shell sort in Data Structure Using CShell sort in Data Structure Using C
Shell sort in Data Structure Using C
Ashish Gaurkhede
 
Sorting Techniques for Data Structures.pptx
Sorting Techniques for Data Structures.pptxSorting Techniques for Data Structures.pptx
Sorting Techniques for Data Structures.pptx
Kalpana Mohan
 
Sorting algorithums > Data Structures & Algorithums
Sorting algorithums  > Data Structures & AlgorithumsSorting algorithums  > Data Structures & Algorithums
Sorting algorithums > Data Structures & Algorithums
Ain-ul-Moiz Khawaja
 
Basics in algorithms and data structure
Basics in algorithms and data structure Basics in algorithms and data structure
Basics in algorithms and data structure
Eman magdy
 

Ähnlich wie Sorting Techniques (20)

Is sort andy-le
Is sort andy-leIs sort andy-le
Is sort andy-le
 
sorting_part1.ppt
sorting_part1.pptsorting_part1.ppt
sorting_part1.ppt
 
Shell sort
Shell sortShell sort
Shell sort
 
Shell sort in Data Structure Using C
Shell sort in Data Structure Using CShell sort in Data Structure Using C
Shell sort in Data Structure Using C
 
Advanced s and s algorithm.ppt
Advanced s and s algorithm.pptAdvanced s and s algorithm.ppt
Advanced s and s algorithm.ppt
 
Cis435 week06
Cis435 week06Cis435 week06
Cis435 week06
 
Analysis and Design of Algorithms -Sorting Algorithms and analysis
Analysis and Design of Algorithms -Sorting Algorithms and analysisAnalysis and Design of Algorithms -Sorting Algorithms and analysis
Analysis and Design of Algorithms -Sorting Algorithms and analysis
 
Data Structures 6
Data Structures 6Data Structures 6
Data Structures 6
 
Sorting Techniques for Data Structures.pptx
Sorting Techniques for Data Structures.pptxSorting Techniques for Data Structures.pptx
Sorting Techniques for Data Structures.pptx
 
Sorting algorithums > Data Structures & Algorithums
Sorting algorithums  > Data Structures & AlgorithumsSorting algorithums  > Data Structures & Algorithums
Sorting algorithums > Data Structures & Algorithums
 
Algorithim lec1.pptx
Algorithim lec1.pptxAlgorithim lec1.pptx
Algorithim lec1.pptx
 
Basics in algorithms and data structure
Basics in algorithms and data structure Basics in algorithms and data structure
Basics in algorithms and data structure
 
Merge sort analysis and its real time applications
Merge sort analysis and its real time applicationsMerge sort analysis and its real time applications
Merge sort analysis and its real time applications
 
Chapter 8 advanced sorting and hashing for print
Chapter 8 advanced sorting and hashing for printChapter 8 advanced sorting and hashing for print
Chapter 8 advanced sorting and hashing for print
 
sorting.pptx
sorting.pptxsorting.pptx
sorting.pptx
 
Data Structures - Lecture 8 [Sorting Algorithms]
Data Structures - Lecture 8 [Sorting Algorithms]Data Structures - Lecture 8 [Sorting Algorithms]
Data Structures - Lecture 8 [Sorting Algorithms]
 
Sorting
SortingSorting
Sorting
 
Radix and Merge Sort
Radix and Merge SortRadix and Merge Sort
Radix and Merge Sort
 
lecture-k-sorting.ppt
lecture-k-sorting.pptlecture-k-sorting.ppt
lecture-k-sorting.ppt
 
3.ppt
3.ppt3.ppt
3.ppt
 

Kürzlich hochgeladen

Salient Features of India constitution especially power and functions
Salient Features of India constitution especially power and functionsSalient Features of India constitution especially power and functions
Salient Features of India constitution especially power and functions
KarakKing
 

Kürzlich hochgeladen (20)

How to Give a Domain for a Field in Odoo 17
How to Give a Domain for a Field in Odoo 17How to Give a Domain for a Field in Odoo 17
How to Give a Domain for a Field in Odoo 17
 
Single or Multiple melodic lines structure
Single or Multiple melodic lines structureSingle or Multiple melodic lines structure
Single or Multiple melodic lines structure
 
Key note speaker Neum_Admir Softic_ENG.pdf
Key note speaker Neum_Admir Softic_ENG.pdfKey note speaker Neum_Admir Softic_ENG.pdf
Key note speaker Neum_Admir Softic_ENG.pdf
 
Accessible Digital Futures project (20/03/2024)
Accessible Digital Futures project (20/03/2024)Accessible Digital Futures project (20/03/2024)
Accessible Digital Futures project (20/03/2024)
 
Interdisciplinary_Insights_Data_Collection_Methods.pptx
Interdisciplinary_Insights_Data_Collection_Methods.pptxInterdisciplinary_Insights_Data_Collection_Methods.pptx
Interdisciplinary_Insights_Data_Collection_Methods.pptx
 
HMCS Max Bernays Pre-Deployment Brief (May 2024).pptx
HMCS Max Bernays Pre-Deployment Brief (May 2024).pptxHMCS Max Bernays Pre-Deployment Brief (May 2024).pptx
HMCS Max Bernays Pre-Deployment Brief (May 2024).pptx
 
REMIFENTANIL: An Ultra short acting opioid.pptx
REMIFENTANIL: An Ultra short acting opioid.pptxREMIFENTANIL: An Ultra short acting opioid.pptx
REMIFENTANIL: An Ultra short acting opioid.pptx
 
SOC 101 Demonstration of Learning Presentation
SOC 101 Demonstration of Learning PresentationSOC 101 Demonstration of Learning Presentation
SOC 101 Demonstration of Learning Presentation
 
Beyond_Borders_Understanding_Anime_and_Manga_Fandom_A_Comprehensive_Audience_...
Beyond_Borders_Understanding_Anime_and_Manga_Fandom_A_Comprehensive_Audience_...Beyond_Borders_Understanding_Anime_and_Manga_Fandom_A_Comprehensive_Audience_...
Beyond_Borders_Understanding_Anime_and_Manga_Fandom_A_Comprehensive_Audience_...
 
Application orientated numerical on hev.ppt
Application orientated numerical on hev.pptApplication orientated numerical on hev.ppt
Application orientated numerical on hev.ppt
 
Graduate Outcomes Presentation Slides - English
Graduate Outcomes Presentation Slides - EnglishGraduate Outcomes Presentation Slides - English
Graduate Outcomes Presentation Slides - English
 
Plant propagation: Sexual and Asexual propapagation.pptx
Plant propagation: Sexual and Asexual propapagation.pptxPlant propagation: Sexual and Asexual propapagation.pptx
Plant propagation: Sexual and Asexual propapagation.pptx
 
Mehran University Newsletter Vol-X, Issue-I, 2024
Mehran University Newsletter Vol-X, Issue-I, 2024Mehran University Newsletter Vol-X, Issue-I, 2024
Mehran University Newsletter Vol-X, Issue-I, 2024
 
Understanding Accommodations and Modifications
Understanding  Accommodations and ModificationsUnderstanding  Accommodations and Modifications
Understanding Accommodations and Modifications
 
Salient Features of India constitution especially power and functions
Salient Features of India constitution especially power and functionsSalient Features of India constitution especially power and functions
Salient Features of India constitution especially power and functions
 
Towards a code of practice for AI in AT.pptx
Towards a code of practice for AI in AT.pptxTowards a code of practice for AI in AT.pptx
Towards a code of practice for AI in AT.pptx
 
UGC NET Paper 1 Mathematical Reasoning & Aptitude.pdf
UGC NET Paper 1 Mathematical Reasoning & Aptitude.pdfUGC NET Paper 1 Mathematical Reasoning & Aptitude.pdf
UGC NET Paper 1 Mathematical Reasoning & Aptitude.pdf
 
General Principles of Intellectual Property: Concepts of Intellectual Proper...
General Principles of Intellectual Property: Concepts of Intellectual  Proper...General Principles of Intellectual Property: Concepts of Intellectual  Proper...
General Principles of Intellectual Property: Concepts of Intellectual Proper...
 
ICT role in 21st century education and it's challenges.
ICT role in 21st century education and it's challenges.ICT role in 21st century education and it's challenges.
ICT role in 21st century education and it's challenges.
 
Wellbeing inclusion and digital dystopias.pptx
Wellbeing inclusion and digital dystopias.pptxWellbeing inclusion and digital dystopias.pptx
Wellbeing inclusion and digital dystopias.pptx
 

Sorting Techniques

  • 1. Insertion Sort & Shellsort By: Andy Le CS146 – Dr. Sin Min Lee Spring 2004
  • 2. Outline  Importance of Sorting  Insertion Sort  Explanation  Runtime  Advantage and Disadvantage  Walk through example  Shell Sort  History  Explanation  Runtime  Advantage and Disadvantage  Walk through example
  • 3. Why we do sorting?  Commonly encountered programming task in computing.  Examples of sorting:  List containing exam scores sorted from Lowest to Highest or from Highest to Lowest  List containing words that were misspelled and be listed in alphabetical order.  List of student records and sorted by student number or alphabetically by first or last name.
  • 4. Why we do sorting?  Searching for an element in an array will be more efficient. (example: looking up for information like phone number).  It’s always nice to see data in a sorted display. (example: spreadsheet or database application).  Computers sort things much faster.
  • 5. History of Sorting  Sorting is one of the most important operations performed by computers. In the days of magnetic tape storage before modern databases, database updating was done by sorting transactions and merging them with a master file.
  • 6. History of Sorting  It's still important for presentation of data extracted from databases: most people prefer to get reports sorted into some relevant order before flipping through pages of data!
  • 7. Insertion Sort  Insertion sort keeps making the left side of the array sorted until the whole array is sorted. It sorts the values seen far away and repeatedly inserts unseen values in the array into the left sorted array.  It is the simplest of all sorting algorithms.  Although it has the same complexity as Bubble Sort, the insertion sort is a little over twice as efficient as the bubble sort.
  • 8. Insertion Sort  Real life example:  An example of an insertion sort occurs in everyday life while playing cards. To sort the cards in your hand you extract a card, shift the remaining cards, and then insert the extracted card in the correct place. This process is repeated until all the cards are in the correct sequence.
  • 9. Insertion Sort runtimes  Best case: O(n). It occurs when the data is in sorted order. After making one pass through the data and making no insertions, insertion sort exits.  Average case: θ(n^2) since there is a wide variation with the running time.  Worst case: O(n^2) if the numbers were sorted in reverse order.
  • 10. Empirical Analysis of Insertion Sort The graph demonstrates the n^2 complexity of the insertion sort. Source: http://linux.wku.edu/~lamonml/algor/sort/insertion.html
  • 11. Insertion Sort  The insertion sort is a good choice for sorting lists of a few thousand items or less.
  • 12. Insertion Sort  The insertion sort shouldn't be used for sorting lists larger than a couple thousand items or repetitive sorting of lists larger than a couple hundred items.
  • 13. Insertion Sort  This algorithm is much simpler than the shell sort, with only a small trade-off in efficiency. At the same time, the insertion sort is over twice as fast as the bubble sort.
  • 14. Advantage of Insertion Sort  The advantage of Insertion Sort is that it is relatively simple and easy to implement.
  • 15. Disadvantage of Insertion Sort  The disadvantage of Insertion Sort is that it is not efficient to operate with a large list or input size.
  • 16. Insertion Sort Example  Sort: 34 8 64 51 32 21  34 8 64 51 32 21  The algorithm sees that 8 is smaller than 34 so it swaps.  8 34 64 51 32 21  51 is smaller than 64, so they swap.  8 34 51 64 32 21
  • 17. Insertion Sort Example  Sort: 34 8 64 51 32 21  8 34 51 64 32 21 (from previous slide)  The algorithm sees 32 as another smaller number and moves it to its appropriate location between 8 and 34.  8 32 34 51 64 21  The algorithm sees 21 as another smaller number and moves into between 8 and 32.  Final sorted numbers:  8 21 32 34 51 64
  • 18. Shellsort  Founded by Donald Shell and named the sorting algorithm after himself in 1959.  1st algorithm to break the quadratic time barrier but few years later, a sub quadratic time bound was proven  Shellsort works by comparing elements that are distant rather than adjacent elements in an array or list where adjacent elements are compared.
  • 19. Shellsort  Shellsort uses a sequence h1, h2, …, ht called the increment sequence. Any increment sequence is fine as long as h 1 = 1 and some other choices are better than others.
  • 20. Shellsort  Shellsort makes multiple passes through a list and sorts a number of equally sized sets using the insertion sort.
  • 21. Shellsort  Shellsort improves on the efficiency of insertion sort by quickly shifting values to their destination.
  • 22. Shellsort  Shellsort is also known as diminishing increment sort.  The distance between comparisons decreases as the sorting algorithm runs until the last phase in which adjacent elements are compared
  • 23. Shellsort  After each phase and some increment hk, for every i, we have a[ i ] ≤ a [ i + hk ] all elements spaced hk apart are sorted.  The file is said to be hk – sorted.
  • 24. Empirical Analysis of Shellsort Source: http://linux.wku.edu/~lamonml/algor/sort/shell.html
  • 25. Empirical Analysis of Shellsort (Advantage)  Advantage of Shellsort is that its only efficient for medium size lists. For bigger lists, the algorithm is not the best choice. Fastest of all O(N^2) sorting algorithms.  5 times faster than the bubble sort and a little over twice as fast as the insertion sort, its closest competitor.
  • 26. Empirical Analysis of Shellsort (Disadvantage)  Disadvantage of Shellsort is that it is a complex algorithm and its not nearly as efficient as the merge, heap, and quick sorts.  The shell sort is still significantly slower than the merge, heap, and quick sorts, but its relatively simple algorithm makes it a good choice for sorting lists of less than 5000 items unless speed important. It's also an excellent choice for repetitive sorting of smaller lists.
  • 27. Shellsort Best Case  Best Case: The best case in the shell sort is when the array is already sorted in the right order. The number of comparisons is less.
  • 28. Shellsort Worst Case  The running time of Shellsort depends on the choice of increment sequence.  The problem with Shell’s increments is that pairs of increments are not necessarily relatively prime and smaller increments can have little effect.
  • 29. Shellsort Examples  Sort: 18 32 12 5 38 33 16 2 8 Numbers to be sorted, Shell’s increment will be floor(n/2) * floor(8/2)  floor(4) = 4 increment 4: 1 2 3 4 (visualize underlining) 18 32 12 5 38 33 16 2 Step 1) Only look at 18 and 38 and sort in order ; 18 and 38 stays at its current position because they are in order. Step 2) Only look at 32 and 33 and sort in order ; 32 and 33 stays at its current position because they are in order. Step 3) Only look at 12 and 16 and sort in order ; 12 and 16 stays at its current position because they are in order. Step 4) Only look at 5 and 2 and sort in order ; 2 and 5 need to be switched to be in order.
  • 30. Shellsort Examples (con’t)  Sort: 18 32 12 5 38 33 16 2 Resulting numbers after increment 4 pass: 18 32 12 2 38 33 16 5 * floor(4/2)  floor(2) = 2 increment 2: 1 2 18 32 12 2 38 33 16 5 Step 1) Look at 18, 12, 38, 16 and sort them in their appropriate location: 12 38 16 2 18 33 38 5 Step 2) Look at 32, 2, 33, 5 and sort them in their appropriate location: 12 2 16 5 18 32 38 33
  • 31. Shellsort Examples (con’t)  Sort: 18 32 12 5 38 33 16 2 * floor(2/2)  floor(1) = 1 increment 1: 1 12 2 16 5 18 32 38 33 2 5 12 16 18 32 33 38 The last increment or phase of Shellsort is basically an Insertion Sort algorithm.
  • 32. Additional Online References  Spark Notes (From Barnes & Noble):  http://www.sparknotes.com/cs/