الوحدة الأولى من المساق، مقدمة لأبرز مفاهيم تراكيب البيانات والمفاهيم العملية المساندة

1. using Java
2015
Data Structure
Prepared by: Mahmoud Rafeek Al-farra
in Java
2. Introduction to data structure

2. mfarra.cst.ps www.fb.com/MahmoudRFarra
Contents
Big - Oh notation
Generic programming
Collection Classes
Applications of data structure
What is data structure ?

3. What is data structure ?
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 Data Structure:
 Abstract way to organize information.
 A collection of basic data types.
 Algorithm:
 Abstract way to perform computation tasks.

4. What is data structure ?
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 Classification of data structure:
Data
Structure
Structure
Linear
Non-Linear
Memory
Allocation
Static
Dynamic

5. Linear data structure
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Linked List
Stack
Queue

6. Non-Linear data structure
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Tree
Graph
Heap

7. Static memory allocation
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 Static memory allocation means the program must
obtain its space before the execution and can not
obtain more while or after execution.
 Example:
 array data structure

8. Dynamic memory allocation
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 The dynamic memory allocation is the ability for a
program to obtain more memory space at execution
time to hold new nodes and to release space no longer
needed.
 Dynamic data structures as:
 Array lists, Vectors
 Linked Lists
 Stacks, Queues
 Trees, Heaps

9. Applications of data structure
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 Priority Queue: in banks, restaurants, …
 Hash Tables: in banks for combining two or more
accounts for matching Social Security Numbers.
 Family Tree
 Country Map
 Queue of tasks
 Order of operations in computer

10. Generic programming
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 Generic programming refers to writing code that will
work for many types of data.
 Generics let you parameterize types.
 With this capability, you can define a class or a
method with generic types that the compiler can
replace with concrete types.

11. Generic programming
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 For example:
 Java defines a generic ArrayList class for
storing the elements of a generic type.
 From this generic class, you can create an
ArrayList object for holding strings and an
ArrayList object for holding numbers.
 Here, strings and numbers are concrete types
that replace the generic type.

12. Collections
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 A Collection is a data type that is capable of holding
a group of items.
 The Collection interface defines the common
operations for lists, vectors, stacks, queues, priority
queues, and sets.
 In Java, Collection classes can be implemented as a
class, along with methods to add, remove, and
examine items.
 Think about a bag

13. Collection Classes
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 A bag can be put in its initial state, which is an empty
bag.
 Numbers can be added into the bag.
 You may check how many occurrences of a certain
number are in the bag.
 Numbers can be removed from the bag.
 You can check how many numbers are in the bag.
All the interfaces and classes defined in the Java Collections
Framework are grouped in the java.util package.

14. Collection Classes
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Examples
Collection classes in Java
Array List
Stack
Queue
List
Linked List
Heap
Sets store a group of nonduplicate elements.
Lists store an ordered collection of elements.
Stacks store objects that are processed in a last-in, first-out fashion.
Queues store objects that are processed in a first-in, first-out fashion.
PriorityQueues store objects that are processed in the order of their priorities.

15. Collection Classes
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16. Collection Test
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import java.util.*;
public class TestCollection {
public static void main(String[] args) {
ArrayList<String> collection1 = new ArrayList<>();
collection1.add("New York");
collection1.add("Atlanta");
System.out.println("A list of cities in collection1:");
System.out.println(collection1);
System.out.println("nIs Dallas in collection1? "+ collection1.contains("Dallas"));
collection1.remove("Dallas");
System.out.println("n" + collection1.size() + " cities are in collection1 now");
Collection<String> collection2 = new ArrayList<>();
collection2.add("Seattle");
collection2.add("Portland");
System.out.println("nA list of cities in collection2:");
System.out.println(collection2);

17. Collection Test
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The Collection interface contains the methods for manipulating the elements
in a collection.

18. Big - Oh notation
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 We might be satisfied with evaluating the performance
or complexity of data structures by precisely counting
the number of statements executed or objects
referenced.
 We adopt special notation to define upper bounds
and lower bounds on functions.
 In CS, usually the functions we are bounding are
running times, memory requirements.

19. Big - Oh notation
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20. using Java
2015
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