1.4.2 Data Structures Flashcards

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1
Q

Arrays

A

An ordered, finite set of elements of a single type

You can make an array of tuples

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2
Q

Index of arrays

A

0-based
Find a value with arrayname[index]
arrayname[row,column] for 2d

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3
Q

Multi-dimensional arrays

A

You can have any number of dimensions

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4
Q

Tuples

A

An ordered set of values, can have elements of mixed type and it is immutable (elements cannot change)

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5
Q

Records

A

Composed of a fixed number of fields of different data types

Access a value with the name of the record

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6
Q

Dynamic data structure

A

They can change size when required

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7
Q

Static data structure

A

They cannot change size

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8
Q

Abstract Data Type

A

A logical description of how we view the data and possible operations

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9
Q

Where does the rear of the queue start at?

A

-1

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10
Q

isFull() pseudocode

A
function isFull()
if size == maxSize:
return True
else:
return False
end if
end function
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11
Q

isEmpty() pseudocode

A
function isEmpty()
if size == 0;
return True:
else: 
return False
end if
end function
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12
Q

enQueue() pseudocode

A
function enQueue()
if size < maxSize:
rear ++
rear = rear MOD maxSize
Q[rear] = item
size ++
else:
print (queue is full)
end if
end function
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13
Q

deQueue() pseudocode

A
function deQueue()
if size  == 0:
item = null
print (queue is empty)
else:
item = Q[front]
front = (front + 1) MOD maxSize
size --
end if
return item
end function
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14
Q

Priority Queue

A

Items are ordered in a queue first based on their priority and then based on FIFO, items move backward to allow a higher priority item to join.

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15
Q

Hash Table

A

A data structure where keys are mapped to index values, used where faster searching is needed e.g. police records

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16
Q

Collisions/synonyms and how to deal with them

A

When an algorithm generates the same address for different primary keys
Methods include putting the value in the next free location or incrementing how far you skip by

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17
Q

Searching in a hash table

A

Apply the hash function to the key and first check that position, if not increment by 1 and check each
If the original position is empty or you cycle back the value isn’t in the table

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18
Q

Mid-square hashing algorithm

A

Square the number, extract some portion of the resulting digits (likely the middle), then mod by the size of the table

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19
Q

Folding hashing algorithm

A

Divide the item into equal sized pieces (excluding maybe the last piece, sum them and carry out the mod with the size of the table

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20
Q

Hashing alphanumeric data

A

Take the ASCII of each character, sum them and mod with the size

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21
Q

Hash table deletion

A

When a value is deleted, a placeholder is used to represent that a value has not been deleted.

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22
Q

Lists

A

A dynamic data type containing a number of ordered items that can be repeated. The elements are stored non-contiguously on the heap and can be of different types

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23
Q

Linked list

A

A dynamic abstract data structure which is implemented as an array and pointers

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24
Q

What is a node composed of linked list?

A

The data and a pointer to the next node

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25
Q

Linked list pointers

A

A start pointer identifies the first element in a list, a nextfree pointer highlights the next free space, the last node has null

26
Q

Stack

A

A collection of elements that are retrieved on a last-in first-out basis

27
Q

Stack variables

A

Top and maxSize

Top starts at -1

28
Q

How to reverse elements?

A

Push them all onto a stack and then pop them off

29
Q

Stack isFull()

A
function isFull()
if (top + 1) == maxSize:
return True
else:
return False
end if
end function
30
Q

Stack isEmpty()

A
function isEmpty()
if top == -1:
return True
else:
return False
end if
end function
31
Q

Stack push()

A
procedure push(newItem)
if (top + 1) == maxSize
print (stack is full)
else:
top ++
stack[top] = newItem
end if
end procedure
32
Q

Stack pop

A
function pop()
if top == -1:
print (stack is empty)
item = null
else:
item = stack[top]
top --
end if
return item
end function
33
Q

Graph

A

A set of vertices connected by edges or arcs

34
Q

Adjacency Matrix of a weighted graph

A

Put the weight of the connecting edge and leave boxes blank instead of writing 0s

35
Q

Adjacency matrix advantages and disadvantages

A

+ convenient to work with, easy to add edges

- wastes a lot of memory space if nodes have few edges

36
Q

Adjacency list

A

A list of nodes pointing to their adjacent nodes

For weighted it has {node:weight}

37
Q

Tree

A

A connected, undirected graph with no cycles

38
Q

Root

A

The node at the top of the tree with no parents

39
Q

Child

A

A node below a parent node in a tree

40
Q

Parent

A

A node above one or more children

41
Q

Subtree

A

A part of a tree which itself is a tree

42
Q

Leaf

A

A node in a tree with no children

43
Q

Binary Tree

A

A rooted tree in which each node has a maximum of two children, each node has a left and a right pointer (-1 if there is no child on that side)

44
Q

Building a binary tree

A

Start from the root each time and trace to the left if the value is smaller than the current node and to the right if it is larger

45
Q

Pre-order searching

A

Visit the root then follow the left subtree then the right

46
Q

In-order searching

A

Follow the left subtree then visit the root then follow the right

47
Q

Post-order searching

A

Traverse the left subtree then the right then visit the root node

48
Q

Deleting a leaf node

A

Just remove the node

49
Q

Deleting a node with one child

A

The child replaces the deleted parent

50
Q

Deleting a node with two children

A

Repeatedly add 1 to the value of the node until you find the value of another node, which will replace the deleted node

51
Q

Binary tree uses

A

Mainly used for searching as you often have to rebuild the tree after deletion

52
Q

Breadth-first traversal

A

Traverses the root then the children of the root left to right then their children left to right

53
Q

Depth first traversal

A

Starts at the bottom left and at each leaf it will move up to the latest decision point and go right where it hasn’t been done before

54
Q

Record declaration

A
Name = record
DataType FieldName
DataType FieldName
…
End record
55
Q

Acessing a record

A

recordName.fieldName

56
Q

Adding a value to the end of a list

A

listName.append(value)

57
Q

Finding the first index of a value in a list

A

listName.index(value)

58
Q

List remove and return from a position

A

listName.pop(index)

59
Q

Removing the first instance of a value from a list

A

listName.remove(value)

60
Q

Initialising a tuple

A

tupleName = (“value1”, “value2”, …)

Accessed like an array

61
Q

Stack peek()

A

Returns the top element if the stack isn’t empty