1. Lesson Objectives Aims – Know about…
Arrays (of up to 3 dimensions), records, lists, tuples.
(b) The following structures to store data: linked-list, graph (directed and undirected), stack, queue, tree, binary search tree, hash table.
(c) How to create, traverse, add data to and remove data from the data structures mentioned above. (NB this can be either using arrays and procedural programming or an object-oriented approach).

2. Data must be stored in any program for it to do something useful
Data structures
Data must be stored in any program for it to do something useful
Selection of correct data type is essential, but correct data structure is equally important
There are two types:
Static
Dynamic

3. Static data structures
Size is pre-determined and set, it cannot be changed in the program
Limited in how useful they can be due to inflexibility and a need to know exact requirements before the program runs
This can be seen as part of how “strongly typed” a language is

4. Strong typing
A strongly typed language will expect all data types to be explicitly defined
This can extend to:
Stating the size of an array
The size of strings (pascal… why?!)
However, this can be a good thing as such code can be considered almost completely “safe” as it is totally predictable and cannot “outgrow” the system limitations
Compilers should catch most typing/casting errors before the code can even run.

5. Dynamic structures
Dynamic data structures allow storage to grow and shrink as necessary
This is obviously preferable – you don’t need to know the exact requirements at compile time
Dynamic structures will have slightly different overheads and requirements to static structures and may also make use of static structures as the “building blocks” of their structure!

6. Array – 1d A basic table Dim colours(4) as string
Each element has an index
Set: colours(2) = “red”
Get: console.writeline(colours(2)) 1 2 3 4
green
Blue
red
Purple
orange

7. Array – 2d A table… Dim SalesFigures(12,3) as decimal (row,column)
Set: SalesFigures(11,2) = “32000” 1 2 3 …. 11
32000 12

8. Array – 3d A set of tables… Dim SalesFigures(3,12,3) as decimal
(table,row,column)
Set: SalesFigures(3,2,5) = “32000”

9. 1D Array
2D Array
3D Array

10. Probably…
In the exam, indexes would be
1D - (index – row)
2D - (column, row)
3D - (table, column, row)
VB is special…

11. Records
A custom data structure which allows data of different types to be stored and accessed through a common name
Person.name = “dave”
Person.weight = 85
VB calls this a “structure” – it’s the same thing

13. Tuples
Like a record but cannot be changed
Can contain data of varying types
Can be referenced by index as an array, but is NOT an array – an array is one data type only.

15. Depends on the language…!
Lists
Depends on the language…!
IF they are static then they work like arrays but allow different types of data to be stored
IF they are dynamic, then…
No fixed size
May have a set data type… may not!

16. Dynamic data structure Each piece of data is a “node” in the list
Linked list
Dynamic data structure
Each piece of data is a “node” in the list
Each node contains a pointer to either:
The next element
Null
The list requires a starting pointer

17. Linked lists
Diagram time…
Adding
Removing
Inserting…?

18. In VB…
Dim myList as new list(of string)
Can be anything – list of objects even.
Mylist.add(item)
Mylist.remove(item)

19. Queues
First in First Out data structure
Can grow and shrink dynamically
Will require a pointer to the “head” and “tail”
Often implemented as a linked list!

20. In vb…
Dim myQ As New Queue() myQ.Enqueue("Hello")’stores at the tail Var = myQ.Dequeue()’gets from head of the queue

21. I’m bored now You lot have done very little recently.
Task 1: make notes on and be ready to explain:
Hash tables
Stacks
Binary Trees
Graphs
You will need code examples in VB too.
I will add YOUR notes to this presentation

22. Then…
Get the programming tasks from the shared area
Do them
I DO expect this handed in, it WILL affect my judgement of your suitability to continue next year.
Really. Code in. Everyone.

23. Uses a hashing algorithm to:
Hash Tables
Uses a hashing algorithm to:
Generate a unique value for given data
This value links to an index in the hash table
This means data can be stored anywhere (basically) in the table, but…
Can be found VERY quickly because a hashing algorithm will produce the same output for a given input.

24. Collisions
In small data sets there is more likelihood of collisions
Collisions are dealt with by creating a linked list (or other suitable data structure) at each entry in the table where there is more than one piece of data to be stored

25. stacks FILO – First in, Last Out Adding data: Remove Data:
Stack must not be full
Otherwise stack overflow
New item added to the top of the stack (Push)
Stack pointer increased by 1
Remove Data:
POP operation
Stack pointer Decreased

26. Uses of Stacks: Backtracking (undo) Reversing data
Storing states (CPU, Interrupts etc)

27. Nodes can be named (parent, child, root, leaf) Storing data:
Binary tree
Made up of nodes (data)
Nodes can be named (parent, child, root, leaf)
Storing data:
Left usually smaller
Right usually larger
Searching:
Starts at root node
Complexity logn

28. Adding nodes
Given this tree…
Add the breed “poodle”

29. Method
Start at root node – Poodle > Harrier
Go down to the next node Poodle < Rottweiler so go LEFT
Next node – Poodle < Pug so go LEFT and add the node to the LEFT underneath PUG

30. Poodle

31. Finding a node
Same method as before – find “Whippet”
Start at root, Whippet > Harrier so go RIGHT
Whippet > Rottweiler so go RIGHT
Node = Whippet = found.

32. Graphs
A structure consisting of Vertices and Edges (nodes and connections)
Connections can be directional
Nodes (vertices) can have multiple connections to other nodes
Used to model real world network like structures such as roads, computer networks, railways etc.
Often used to calculate distances/times and so on – Logistical operations!

33. Review/Success Criteria