1. Programming Fundamentals
Session III
Master a Skill / Learn for Life

2. Session Outline Data Structures Algorithms
Chapter 1 - Structures and Arrays
Chapter 2 - Sets and Linked List
Chapter 3 - Collections and Dictionaries
Chapter 4 - Stack, Queues, and Deques
Chapter 5 - Graphs and Trees
Algorithms
Chapter 1 - Sorting Algorithm
Chapter 2 - Searching Algorithms
Chapter 3 - String Searching
Chapter 4 - Data Compression Algorithms
Chapter 5 - Encryption Algorithm
11/10/2018
Copyright © Carl M. Burnett

3. Data Structures Chapter 1 - Structures and Arrays
Chapter 2 - Sets and Linked Lists
Chapter 3 - Collections and Dictionaries
Chapter 4 - Stacks, Queues, Disques
Chapter 5 - Graphs and Trees
11/10/2018
Copyright © Carl M. Burnett

4. Structures and Arrays Structure – Record = Database record Array:
Series or list of variables in computer memory
All share the same name
Each has a different subscript
Subscript (or index):
Position number of an item in an array
Subscripts are always a sequence of integers
11/10/2018
Copyright © Carl M. Burnett

5. Dim NameArray(15) as String
Defining an Array
Variable Name
Array Size – Number of Items to Store
Type of Data – Integer or String
Dim NameArray(15) as String
11/10/2018
Copyright © Carl M. Burnett

6. How Arrays Occupy Computer Memory
Each item has same name and same data type
Element: an item in the array
Array elements are contiguous in memory
Size of the array: number of elements it will hold 25
someVal[0] 36
someVal[1] 47
someVal[2] 15
aNumber
11/10/2018
Copyright © Carl M. Burnett

7. How Arrays Occupy Computer Memory
Subscript is placed in parentheses or square brackets following the array name (language-dependent)
Zero-based array:
First subscript is 0
Highest subscript value is 1 less than the array size
Arrays make programs more efficient and professional
11/10/2018
Copyright © Carl M. Burnett

8. Defining Size Bounds Default Bounds Lower Bound - First Element
Upper Bound – Last Element
Default Bounds
C and Java = Starts with 0 (Zero-Based Array)
Other Language = Start with 1 (One-based Array)
11/10/2018
Copyright © Carl M. Burnett

9. Dim LotteryNumbers(5) as Integer
Defining Size 1 2 3 4
Zero-Based Array 1 2 3 4 5
One-Based Array
Dim LotteryNumbers(5) as Integer
11/10/2018
Copyright © Carl M. Burnett

10. Dim LotteryNumbers(33..37) as Integer
Defining Bounds
Dim LotteryNumbers(33..37) as Integer 33 34 35 36 37
11/10/2018
Copyright © Carl M. Burnett

11. Array Declaration and Initialization
Programming Language
DIM COUNT(30)
BASIC, Visual Basic
int count(30);
C#, C++
int() count = new int(30);
Java
COUNT OCCURS 30 TIMES PICTURE 9999.
COBOL
Array count (1…30) of integer;
Pascal
Array elements do not have to be declared individually
Put the array size in square brackets in the declaration
11/10/2018
Copyright © Carl M. Burnett

12. Array Declaration and Initialization
Array elements should be initialized
Initialization loop: loop structure that provides initial values to an array
Use the loop control variable as the array subscript
11/10/2018
Copyright © Carl M. Burnett

13. Array Declaration and Initialization
Basic
Dim LotteryNumbers(5) as Integer
For I = 1 to 5
LotteryNumbers(1) = 0
Next I
C++
Int lotterynumbers[] = (0, 0, 0, 0, 0);
11/10/2018
Copyright © Carl M. Burnett

14. Storing Data in Array The Array Name Array Element Basic
Dim myarray(5) as Integer
myarray(1) = 357
C++
Int myarray[5];
myarray[0] = 357;
Int myarray[5];
myarray[0] = 47;
myarray[3] = 91;
myarray[1] = 6;
11/10/2018
Copyright © Carl M. Burnett

15. Retrieving Data Basic Dim Names(3) as String
Names(1) = “George Washington”
Names(2) = “John Adams”
Names(3) = “Thomas Jefferson”
Print Names (2)
This prints the name John Adams on screen.
11/10/2018
Copyright © Carl M. Burnett

16. Multi-Dimensional Arrays
Sometime known as a Data Grid
BigArray (1,1)
BigArray (1,2)
BigArray (2,1)
BigArray (2,2)
BigArray (3,1)
BigArray (3,2)
BigArray (4,1)
BigArray (4,2)
Basic
Dim BigArray(4,2) as String
Dim BigArray(2,4,3,8) as String
C++
string BigArray[4][2];
string BigArray[2][4][3][8];
11/10/2018
Copyright © Carl M. Burnett

17. Multi-Dimensional Arrays
Storing and Getting Data
Dim BigArray(4,2) as String
BigArray(4,1) = “Grover Cleveland”
Print BigArray(4,1)
This prints the name Grover Cleveland on screen.
11/10/2018
Copyright © Carl M. Burnett

18. Array Drawbacks Large Arrays take up more space
Arrays can hold only one data type
Searching and sorting is difficult
Inserting and removing data is cumbersome
11/10/2018
Copyright © Carl M. Burnett

19. Sets and Linked Lists Arrays stores integers.
You may need to create resizable (dynamic) arrays.
Arrays stores a special Variant data type - both numbers and text.
Many programming languages allow you to create other types of data structures.
Two popular alternatives to arrays are:
Sets
Linked Lists
11/10/2018
Copyright © Carl M. Burnett

20. Sets Advantages No definition of fixed size.
An array to hold seven separate variables like this:
Dim Day(6) as String
Day(0) = "Monday" Day(1) = "Tuesday"
Day(2) = "Wednesday"
Day(3) = "Thursday"
Day(4) = "Friday"
Day(5) = "Saturday"
Day(6) = "Sunday"
From set import sets
days = Set ([‘Monday’, ‘Tuesday’, ‘Wednesday’, ‘Thursday’, ‘Friday’, ‘Saturday’, ‘Sunday’])
Advantages
No definition of fixed size.
No ID of index number for data
Can use mixed data types
11/10/2018
Copyright © Carl M. Burnett

21. Linked Lists It is a data structure Group of nodes
Represent a sequence.
A linear collection of data elements
Pointer - Points to the next node by means of a pointer.
Variables
Variables hold data
Pointer
A pointer points to another node
11/10/2018
Copyright © Carl M. Burnett

22. Linked Lists Advantages Disadvantages
dynamic data structure - can grow and be pruned, allocating and deallocating memory
Insertion and deletion node operations are easily implemented in a linked list.
Dynamic data structures such as stacks and queues can be implemented using a linked list.
There is no need to define an initial size for a Linked list.
Items can be added or removed from the middle of list.
Disadvantages
They use more memory than arrays
Nodes must be read in order - sequential access.
Nodes are stored incontiguously - greatly increasing the access time required.
Difficulties in reverse traversing.
11/10/2018
Copyright © Carl M. Burnett

23. Collections A grouping of some variable number of data items
Shared significance to the problem being solved
Need to be operated upon together in some controlled fashion.
Like a resizable array.
Can hold different data types.
Collections include:
Lists
Sets
Multisets
Trees
graphs
Implementations include:
C++: known as "container“
Java: implemented in the Java collections framework;
Python: some built-in, others implemented in the collections library.
11/10/2018
Copyright © Carl M. Burnett

24. Dictionaries An associative array, map, symbol table.
Abstract data type
Composed of a collection of (key, value) pairs.
Operations associated with this data type allow:
the addition of a pair to the collection
the removal of a pair from the collection
the modification of an existing pair
the lookup of a value associated with a particular key
11/10/2018
Copyright © Carl M. Burnett

25. Dictionaries Language support
Dictionaries - Smalltalk, Objective-C, .NET,[13] Python, REALbasic, Swift, and VBA.
Hashes - Perl, Ruby and Seed7
Maps - C++, Java, Go, Clojure, Scala, OCaml, Haskell,
Hash tables - Common Lisp and Windows PowerShell
Associative Arrays - PHP
Objects – JavaScript, JSON (All objects behave as associative arrays with string-valued keys.
11/10/2018
Copyright © Carl M. Burnett

26. Stacks
11/10/2018
Copyright © Carl M. Burnett

27. Queues & Deques
11/10/2018
Copyright © Carl M. Burnett

28. Graphs Data structure: Vertices or Nodes or Points
Connections - set of unordered pairs of these vertices
11/10/2018
Copyright © Carl M. Burnett

29. Graphs Abstract Data Type Undirected graph Directed graph5 2 3 9
Directed graph 6
Weighted graph 8 3 1 7
11/10/2018
Copyright © Carl M. Burnett

30. Trees Simulates a hierarchical tree structure A root value
Subtrees of children with a parent node
Represented as a set of linked nodes.
11/10/2018
Copyright © Carl M. Burnett

31. Trees Edge - The connection between one node and another.
Path - A sequence of nodes and edges connecting a node with a descendant.
Level - The level of a node is defined by 1 + (the number of connections between the node and the root).
Height of node - The height of a node is the number of edges on the longest path between that node and a leaf.
Height of tree - The height of a tree is the height of its root node.
Depth - The depth of a node is the number of edges from the tree's root node to the node.
Forest - A forest is a set of n ≥ 0 disjoint trees.
Root - The top node in a tree.
Child - A node directly connected to another node when moving away from the Root.
Parent - The converse notion of a child.
Siblings - A group of nodes with the same parent.
Descendant - A node reachable by repeated proceeding from parent to child.
Ancestor - A node reachable by repeated proceeding from child to parent.
Leaf (External node) - A node with no children.
Branch (Internal node) - A node with at least one child.
Degree - The number of sub trees of a node.
11/10/2018
Copyright © Carl M. Burnett

32. Algorithms Sorting Algorithms Searching Algorithms
String Searching Algorithms
Data Compression Algorithms
Encryption Algorithms
11/10/2018
Copyright © Carl M. Burnett

33. Sorting Algorithms Comparison of Different Sorting Algorithms
Average
Best
Worst
Bubble Sort
O(n^2)
Selection Sort
Insertion Sort
O(n)
Heap Sort
O(n*log(n))
Merge Sort
Quick Sort
11/10/2018
Copyright © Carl M. Burnett

34. Searching Algorithms Category of Searching Algorithms
Uninformed (Brute-Force)
Informed (Heuristic)
11/10/2018
Copyright © Carl M. Burnett

35. Sequential Search Algorithms
Uninformed Algorithm
Backward or Forward
Block
Binary
Interpolation
11/10/2018
Copyright © Carl M. Burnett

36. Informed Searching Indexes Adversarial Search Alpha-bets Pruning
Clustered Index
Unclustered Index
Adversarial Search
Alpha-bets Pruning
11/10/2018
Copyright © Carl M. Burnett

37. String Searching Algorithms
Sequential Text
Boyer-Moore Algorithm
Rabin-Karp Algorithm
Shift Or Algorithm
Regular Expressions
Multiple Character Patterns
Alternate Patterns
Phonetically
11/10/2018
Copyright © Carl M. Burnett

38. Data Compression Algorithms
Lossless Data Compression
Run-Length Encoding (RLE)
Burrow-Wheeler Algorithm
Dictionary Encoding
LZ77 Algorithm
LZW Algorithm
Lossy Data Compression
11/10/2018
Copyright © Carl M. Burnett

39. Encryption Algorithms
Stream Ciphers
Block Ciphers
Electronic Code Book (ECB)
Cipher-block Chaining (CBC)
Symmetrical Encryption
Asymmetrical Encryption
Hash Functions
11/10/2018
Copyright © Carl M. Burnett

40. Student Exercise
Continue to work on your Getting Dressed Program. Identify and create a data dictionary for all the data types used in your process. These include:
Data Variables
Arrays
Collections
Classes
Objects
Metadata
11/10/2018
Copyright © Carl M. Burnett

41. Next – Web Programming & Web Programming Languages
Session Review
Data Structures
Chapter 1 - Structures and Arrays
Chapter 2 - Sets and Linked List
Chapter 3 - Collections and Dictionaries
Chapter 4 - Stack, Queues, and Deques
Chapter 5 – Graphs and Trees
Algorithms
Chapter 1 - Sorting Algorithm
Chapter 2 - Searching Algorithms
Chapter 3 - String Searching
Chapter 4 - Data Compression Algorithms
Chapter 5 - Encryption Algorithm
Next – Web Programming & Web Programming Languages
11/10/2018
Copyright © Carl M. Burnett