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## PowerPoint Slideshow about ' Arrays' - sumana

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Arrays and Their Properties

Hold several values of the same type (homogeneous)

Based on a slot number (the index number)

Instant access

Linear (one after the other)

Static – once their size is set, it’s set…

What arrays look like

Things to notice

There are 7 slots, with index numbers 0 – 6

The name of the array is myArray

Easy to be off by one

1

2

3

4

5

6

0

myArray

Creating Arrays

<data type>[] <name> = new <data type> [<size>];

new brings complex variables to life in C#

Notice that we can create an array of any data type, just by changing the data type!

Examples

An array of shorts:

short[] someArray = new short[50];

An array of floats:

float[] myArray = new float[25];

An array of booleans:

bool[] list = new bool[65];

An array of chars:

char[] characters = new char[255];

Initializing Arrays with Values

<data type>[] <name> = new <data type> [<size>] {VALUES};

Or

<data type>[] <name> = {VALUES};

Modifying an Array

You must specify which slot you are putting information in

Example:

int[] myArray = new int[50];

myArray[3] = 12;

This won’t work:

int[] myArray = new int[50];

myArray = 12;

Data type on the left of = is an array

Data type on right of = is an int

0

1

2

3

4

49

…

12

Accessing Information

Copying information out of a particular slot

Example:

int clientAge;

clientAge = myArray[4];

This copies information from the fifth slot (slot four) into the variable clientAge

Initializing Arrays(large arrays)

For most arrays, you will use a loop to initialize

Problem: create an array of 50 bytes and fill each slot with the number 42

Solution:

byte[] myList = new byte[50];

for (int counter=0; counter < 50; counter++) {

myList[counter] = 42;

}

Searching Arrays

- Sequential
- What if array is sorted
- Binary

Searching

- Searching is the process of finding a target element within a group of items called the search pool
- The target may or may not be in the search pool
- We want to perform the search efficiently, minimizing the number of comparisons
- Let's look at two classic searching approaches: linear search and binary search

Sequential Search

- A Sequential Search can be used to determine if a specific value (the search key) is in an array.
- Approach is to start with the first element and compare each element to the search key:
- If found, return the index of the element that contains the search key.
- If not found, return -1.
- Because -1 is not a valid index, this is a good return value to indicate that the search key was not found in the array.

Code to Perform a Sequential Search

public int findWinners( int key )

{

for ( int i = 0; i < winners.length; i++ )

{

if ( winners[i] == key )

return i;

}

return -1;

}

Sequential Search of a Sorted Array

- When the array is sorted, we can implement a more efficient algorithm for a sequential search.
- If the search key is not in the array, we can detect that condition when we find a value that is higher than the search key.
- All elements past that position will be greater than the value of that element, and therefore, greater than the search key.

Sample Code

public intsearchSortedArray( int key )

{

for ( inti = 0; i < array.length

&&array[i] <= key; i++ )

{

if ( array[i] == key )

return i;

}

return –1; // end of array reached without

// finding keyor

// an element larger than

// the key was found

}

Binary Search

- A Binary Search is like the "Guess a Number" game.
- To guess a number between 1 and 100, we start with 50 (halfway between the beginning number and the end number).
- If we learn that the number is greater than 50, we immediately know the number is not 1 - 49.
- If we learn that the number is less than 50, we immediately know the number is not 51 - 100.
- We keep guessing the number that is in the middle of the remaining numbers (eliminating half the remaining numbers) until we find the number.

Binary Search

- The "Guess a Number" approach works because 1 - 100 are a "sorted" set of numbers.
- To use a Binary Search, the array must be sorted.
- Our Binary Search will attempt to find a search key in a sorted array.
- If the search key is found, we return the index of the element with that value.
- If the search key is not found,we return -1.

The Binary Search Algorithm

- We begin by comparing the middle element of the array and the searchkey.
- If they are equal, wefound the searchkey and return the index of the middle element.
- If the middle element's value isgreaterthan the searchkey, then the searchkeycannotbefound in elementswithhigherarray indexes. So, we continue oursearch in the lefthalf of the array.
- If the middle element's value islessthan the searchkey, then the searchkeycannotbefound in elementswithlowerarray indexes. So, we continue oursearch in the right half of the array.

The Binary Search Algorithm (con't)

- As we keep searching, the subarray we search keeps shrinking in size. In fact, the size of the subarray we search is cut in half at every iteration.
- If the search key is not in the array, the subarray we search will eventually become empty. At that point, we know that we will not find our search key in the array, and we return –1.

Example of a Binary Search

- For example, we will search for the value 7 in this sorted array:
- To begin, we find the index of the center element, which is 8, and we compare our search key (7) with the value 45.

Binary Search Example (con't)

- Because 7 is less than 35, we eliminate all array elements higher than our current middle element and consider elements 0 through 7 the new subarray to search.
- The index of the center element is now 3, so we compare 7 to the value 8.

Binary Search Example (con't)

- Because 7 is less than 8, we eliminate all array elements higher than our current middle element (3) and make elements 0 through 2 the new subarray to search.
- The index of the center element is now 1, so we compare 7 to the value 6.

Binary Search: Finding the search key

- Because 7 is greater than 6, we eliminate array elements lower than our current middle element (1) and make element 2 the new subarray to search.
- The value of element 2 matches the search key, so our search is successful and we return the index 2.

Binary Search Example 2

- This time, we search for a value not found in the array, 34. Again, we start with the entire array and find the index of the middle element, which is 8.
- We compare our search key (34) with the value 45.

Binary Search Example 2 (con't)

- Because 34 is less than 45, we eliminate array elements higher than our current middle element and consider elements 0 through 7 the new subarray to search.
- The index of the center element is now 3, so we compare 34 to the value 8.

Binary Search Example 2 (con't)

- Because 34 is greater than 8, we eliminate array elements lower than our current middle element and consider elements 4 through 7 the new subarray to search.
- The index of the center element is now 5, so we compare 34 to the value 15.

Binary Search Example 2 (con't)

- Again, we eliminate array elements lower than our current middle element and make elements 6 and 7 the new subarray to search.
- The index of the center element is now 6, so we compare 34 to the value 22.

Binary Search 2: search key is not found

- Next, we eliminate array elements lower than our current middle element and make element 7 the new subarray to search.
- We compare 34 to the value 36, and attempt to eliminate the higher subarray, which leaves an empty subarray.
- We have determined that 32 is not in the array. We return -1 to indicate an unsuccessful search.

Binary Search Code

public intbinarySearch( int [] array, int key )

{

int start = 0, end = array.length - 1;

while ( end >= start )

{

int middle = ( start + end ) / 2;

if ( array[middle] == key )

return middle; // key found

else if ( array[middle] > key )

end = middle - 1; // search left

else

start = middle + 1; // search right

}

return -1; // key not found

}

Sorting

- Sorting is the process of arranging a list of items in a particular order
- The sorting process is based on specific value(s)
- sorting a list of test scores in ascending numeric order
- sorting a list of people alphabetically by last name

- There are many algorithms, which vary in efficiency, for sorting a list of items

Sorting

- When an array's elements are in random order, our Sequential Searchmethod needs to look at every element in the array before discovering that the search key is not in the array. This is inefficient; the larger the array, the more inefficient a Sequential Searchbecomes.
- We could simplify the search by arranging the elements in numeric order, which is called sorting the array. Once the array is sorted, we can use various search algorithms to speed up a search, including binary search.

Sorting

- We will review three different sorts:
- Selection Sort
- Bubble Sort
- Insertion Sort

Selection Sort

- In a Selection Sort, we select the smallest element in the array and place it at the beginning of the array. Then we select the next-smallest element and put it in the second position in the array, and so on.
- To do this, we consider the unsorted portion of the array as a subarray. Werepeatedly select the smallest value in the currentsubarray and move it to the beginning of the subarray, thenconsider a new subarray by eliminating the elementsthat are in theirsorted locations. We continue until the subarray has only one element. Atthat time, the arrayissorted.

The Selection Sort Algorithm

To sort an arraywithnelements in ascendingorder:

1. Consider the nelements as a subarraywithm = nelements.

2. Find the index of the smallest value in thissubarray.

3. Swap the values of the elementwith the smallest value and the element in the first position in the subarray.

4. Consider a new subarray of m = m - 1 elements by eliminating the first element in the previoussubarray

5. Repeatsteps 2 through 4 untilm = 1.

Selection Sort

- Algorithm:
for index = 0 to length-2 do

for index2 = index to length -1 do

find minimum value

swap minimum value with list[index]

Swapping Values

- To swap two values, we define a temporary variable to hold the value of one of the elements, so that we don't lose that value during the swap.
To swap elements a and b:

- define a temporary variable, temp.
- assign element a to temp.
- assign element b to element a.
- assign temp to element b.

Swapping Example

- This code will swap elements 3 and 6 in an int array named array:
int temp; // step 1

temp = array[3]; // step 2

array[3] = array[6]; // step 3

array[6] = temp; // step 4

The picture shows an array of six integers that we want to sort from smallest to largest.

Sorting Integers[0][1] [2] [3] [4] [5]

Start by finding the sort from smallest to largest.smallest entry.

Selection Sort Algorithm[0][1] [2] [3] [4] [5]

Start by finding the sort from smallest to largest.smallest entry.

Swap the smallest

entry with the

first entry.

Selection Sort Algorithm[0][1] [2] [3] [4] [5]

Selection Sort Algorithm sort from smallest to largest.

- Start by finding the smallest entry.
- Swap the smallest
- entry with the
- first entry.

[0][1] [2] [3] [4] [5]

Part of the array is now sorted. sort from smallest to largest.

Selection Sort AlgorithmSorted side

Unsorted side

[0][1] [2] [3] [4] [5]

Find the smallest element in the unsorted side. sort from smallest to largest.

Selection Sort AlgorithmSorted side

Unsorted side

[0][1] [2] [3] [4] [5]

Find the smallest element in the unsorted side. sort from smallest to largest.

Swap with the front of the unsorted side.

Selection Sort AlgorithmUnsorted side

Sorted side

[0][1] [2] [3] [4] [5]

We have increased the size of the sorted side by one element.

Selection Sort AlgorithmSorted side

Unsorted side

[0][1] [2] [3] [4] [5]

The process continues... element.

Selection Sort AlgorithmSorted side

Unsorted side

Smallest

from

unsorted

[0][1] [2] [3] [4] [5]

The process continues element.

...

Selection Sort AlgorithmSorted side

Unsorted side

Swap

with

front

[0][1] [2] [3] [4] [5]

The process continues element.

...

Selection Sort AlgorithmSorted side

is bigger

Sorted side

Unsorted side

[0][1] [2] [3] [4] [5]

The process keeps adding one more number to the sorted side. element.

The sorted

side has the smallest numbers, arranged from small to large.

Selection Sort AlgorithmSorted side

Unsorted side

[0][1] [2] [3] [4] [5]

We can stop element.

when the

unsorted

side has just

one number,

since that

number

must be the

largest

number.

Sorted side

Unsorted side

Selection Sort Algorithm[0][1] [2] [3] [4] [5]

The array is now sorted. element.

We repeatedly selected the smallest element, and moved this element to the front of the

unsorted

side.

Selection Sort Algorithm[0][1] [2] [3] [4] [5]

Bubble Sort element.

- The basic approach to a Bubble Sort is to make multiple passes through the array.
- In each pass, we compare adjacent elements. If any two adjacent elements are out of order, we put them in order by swapping their values.
- At the end of each pass, one more element has "bubbled" up to its correct position.
- We keep making passes through the array until all the elements are in order.

Bubble Sort Algorithm element.

- To sort an array of nelements in ascendingorder, we use a nestedloop:
- The outerloopexecutesn – 1 times.
- For eachiteration of the outerloop, the innerloopstepsthrough all the unsortedelements of the array and does the following:
- Compares the currentelementwith the nextelement in the array.
- If the nextelementissmaller, it swaps the twoelements.

Bubble Sort Pseudocode element.

for i = 0 to last array index – 1 by 1

{

for j = 0 to ( last array index – i - 1 ) by 1

{

if ( 2 consecutive elements are not in order )

swap the elements

}

}

Bubble Sort Example element.

- At the beginning, the array is:
- We compare elements 0 (17) and 1 (26) and find they are in the correct order, so we do not swap.

Bubble Sort Example (con't) element.

- The inner loop counter is incremented to the next element:
- We compare elements 1 (26) and 2 (5), and find they are not in the correct order, so we swap them.

Bubble Sort Example (con't) element.

- The inner loop counter is incremented to the next element:
- We compare elements 2 (26) and 3 (2), and find they are not in the correct order, so we swap them.
- The inner loop completes, which ends our first pass through the array.

Bubble Sort Example (2 element.nd pass)

- The largest value in the array (26) has bubbled up to its correct position.
- We begin the second pass through the array. We compare elements 0 (17) and 1 (5) and swap them.

Bubble Sort Example (2 element.nd pass)

- We compare elements 1 (17) and 2 (2) and swap.
- This ends the second pass through the array. The second-largest element (17) has bubbled up to its correct position.

Bubble Sort (3 element.rd pass)

- We begin the last pass through the array.
- We compare element 0 (5) with element 1 (2) and swap them.

Bubble Sort ( complete ) element.

- The third-largest value (5) has bubbled up to its correct position.
- Only one element remains, so the array is now sorted.

Bubble Sort Code element.

for ( inti = 0; i < array.length - 1; i++ )

{

for ( int j = 0; j < array.length – i - 1; j++ )

{

if ( array[j] > array[j + 1] )

{

// swap the elements

int temp = array[j + 1];

array[j + 1] = array[j];

array[j] = temp;

}

} // end inner for loop

} // end outer for loop

The element.Bubblesort algorithm compares adjacent elements and exchanges them if they are out of order.

Bubble Sort Algorithm[0][1] [2] [3] [4] [5]

The first two elements are compared, and are out of order, so they are exchanged.

Bubble Sort Algorithm[0][1] [2] [3] [4] [5]

The first two elements are compared, and are out of order, so they are exchanged.

Bubble Sort Algorithm[0][1] [2] [3] [4] [5]

Now the next two elements are compared. They are in order, so no exchange.

Bubble Sort Algorithm[0][1] [2] [3] [4] [5]

And the process continues…another exchange. so no exchange.

Bubble Sort Algorithm[0][1] [2] [3] [4] [5]

And the process continues…another exchange. so no exchange.

Bubble Sort Algorithm[0][1] [2] [3] [4] [5]

And the process continues so no exchange.…

Another exchange.

Bubble Sort Algorithm[0][1] [2] [3] [4] [5]

And the process continues so no exchange.… another exchange. The biggest element is now in place.

Bubble Sort Algorithm[0][1] [2] [3] [4] [5]

Now repeat from the first position to so no exchange.

length -1.

Bubble Sort Algorithm[0][1] [2] [3] [4] [5]

Process continues so no exchange.… exchange occurs. At this point, the last two elements are in their final sorted order.

Bubble Sort Algorithm[0][1] [2] [3] [4] [5]

Repeat again from the beginning. Exchange must occur. so no exchange.

Bubble Sort Algorithm[0][1] [2] [3] [4] [5]

Repeat again from the beginning. Exchange must occur. so no exchange.

Bubble Sort Algorithm[0][1] [2] [3] [4] [5]

Insertion Sort so no exchange.

- The basic approach to Insertion Sort is to make multiple passes through the array.
- In each pass, we “insert” the first element in the unsorted side into its correct sorted position in the sorted side.
- At the end of each pass, all the elements in the “sorted” side are sorted in relation to one another, but may not be in their final sorted position.
- We keep making passes through the array until all the elements are in order.

Insertion Sort so no exchange.

- Algorithm:
for index = 0 to length-1 do

Item = list[index]

index2 = index -1

placefound = false

while not placefound and index2 >=0

if item < list[index2] then

list[index2 + 1] = list[index2]

index2 = index2 - 1

else

placefound = true

list[index2 +1] = item;

The so no exchange.Insertionsort algorithm also views the array as having a sorted side and an unsorted side.

Insertion Sort Algorithm[0][1] [2] [3] [4] [5]

The sorted so no exchange.

side starts

with just the

first element,

which is not

necessarily

the smallest

element.

Insertion Sort AlgorithmSorted side

Unsorted side

[0][1] [2] [3] [4] [5]

The sorted so no exchange.

side grows

by taking

the front

element

from the

unsorted

side...

Sorted side

Unsorted side

Insertion Sort Algorithm[0][1] [2] [3] [4] [5]

...and so no exchange.

inserting it in

the place

that keeps

the sorted

side

arranged

from small

to large.

Insertion Sort AlgorithmUnsorted side

Sorted side

[0][1] [2] [3] [4] [5]

In this so no exchange.example,

the new element

goes in front of the element that was already in the sorted side.

Insertion Sort AlgorithmUnsorted side

Sorted side

[0][1] [2] [3] [4] [5]

Sometimes so no exchange.

we are lucky

and the new

inserted item

doesn't need

to move at

all.

Sorted side

Unsorted side

Insertion Sort Algorithm[0][1] [2] [3] [4] [5]

Sometimes we are lucky twice in a row. so no exchange.

Sorted side

Unsorted side

Insertion Sort Algorithm[0][1] [2] [3] [4] [5]

Copy the new element to a separate location. so no exchange.

Sorted side

Unsorted side

Insertion Sort Algorithm[0][1] [2] [3] [4] [5]

Shift elements in the sorted side, creating an open space for the new element.

How to Insert One Element[0][1] [2] [3] [4] [5]

Shift elements in the sorted side, creating an open space for the new element.

How to Insert One Element[0][1] [2] [3] [4] [5]

...until you reach the location for the new element. for the new element.

How to Insert One Element[0][1] [2] [3] [4] [5]

Copy the new element back into the array, at the correct location.

Sorted side

Unsorted side

How to Insert One Element[0][1] [2] [3] [4] [5]

The last element must also be inserted. Start by copying it...

Sorted side

Unsorted side

How to Insert One Element[0][1] [2] [3] [4] [5]

How many shifts will occur before we copy this element back into the array? (Value is 15.)

Self Test[0][1] [2] [3] [4] [5]

Four items are shifted. into the array? (Value is 15.)

And then the element is copied back into the array.

Self Test[0][1] [2] [3] [4] [5]

Questions? into the array? (Value is 15.)

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