1. Data Structures & File Processing
Topic 1 Introduction and Overview

2. Basic Terminology; Elementary Data Organization
Data – values/set of values.
Data item – single unit of values.
Group items – divided into subitems.
Elementary items – not divided.
E.g., employee name may be divided into three subitems – first name, middle initial and last name – social security number – single item.

3. Basic Terminology; Elementary Data Organization
Entity – something that has attributes/properties which may be assigned values.
Values may be numeric/nonnumeric.
Entities with similar attributes (e.g., all employees in organization) form entity set.
Attributes:
Name
Age
Sex
Social Security Number
Values:
Rumaisya, Saifi 34 F

4. Basic Terminology; Elementary Data Organization
Each attribute of entity set has range of values – set of all possible values that could be assigned to the particular attribute.
Term “information” sometimes used for data with given attributes, or, in other words, meaningful or processed data.

5. Basic Terminology; Elementary Data Organization
Field – single elementary unit of information representing entity attribute.
Record – collection of field values of an entity.
File – collection of entities records in an entity set.

6. Basic Terminology; Elementary Data Organization
Each record in file may contain many field items, but the value in a certain field may uniquely determine the record in the file.
Such a field K is called a primary key, and values k1, k2, … in such a field are called keys or key values.

7. Basic Terminology; Elementary Data Organization
Example:
Automobile dealership inventory file, each record contains:
Serial Number, Type, Year, Price, Accessories
Primary key? Since each automobile has unique serial number

8. Basic Terminology; Elementary Data Organization
Example:
Organization membership file, each record contains:
Name, Address, Telephone Number, Dues Owed
Group items – Name, Address
Primary key – Name
Address and Telephone Number may not serve as primary key

9. Basic Terminology; Elementary Data Organization
Records may also be classified according to length.
File can have:
Fixed-length records – all records contain same data items with same amount of space
Variable-length records – different lengths of records. E.g., student records since different students take different number of courses. Usually have minimum and maximum length.

10. Data Structures
Data structure – logical or mathematical model of a particular organization of data.
Choice of data model depends on:
Richness in structure to mirror actual relationships of data in real world
Simplicity, one can effectively process data when necessary

11. Classification of Data Structures

12. Arrays Linear (or dimensional) array
List of finite number n of similar data elements referenced by a set of n consecutive numbers, usually 1, 2, 3, …, n.
Array name A, elements of A denoted by subscript
a1, a2, a3, …, an
A(1), A(2), A(3), …, A(N)
A[1], A[2], A[3], …, A[N]

13. Arrays Number K in A[K] is called subscript
A[K] is called subscripted variable
Linear arrays are called one-dimensional arrays because each element in array is referenced by one subscript.

14. Arrays
List weekly sales can be stored in two-dimensional array, first subscript denotes store and second subscript the department.
SALES is the name given to the array

15. Linked List
Brokerage firm

16. Linked List
Integer used as a pointer requires less space than a name

17. Linked List
Suppose the firm wants the list of customers for a given salesperson
Using Fig. 1.5, the firm would have to search through the entire customer file

18. Linked List
Disadvantage: each salesperson have many pointers and the set of pointers change as customers are added and deleted.

19. Linked List

20. Trees
Rooted tree graph/tree – data contain hierarchical relationship between elements

21. Trees Example Record Structure:
Employee personnel record contain data items:
Social Security Number, Name, Address, Age, Salary, Dependents
Group item
Subitem
Name
Last, First, MI (middle initial)
Address
Street, Area
Area
City, State, ZIP code number

23. Trees Example Algebraic Expression: (2x + y)(a – 7b)3
Exponentiation – vertical arrow (↑)
Multiplication – asterisk (*)

24. Trees
Exponentiation take place after subtraction, multiplication at top of tree executed last.

25. Stack
Also called last-in first-out (LIFO) system – linear list which insertions and deletions take place only at one end, called top
New dishes inserted at top of stack and deleted only from top of stack

26. Queue
Also called first-in first out (FIFO) system – linear list which deletions take place only at one end of list, “front” of list, and insertions take place only at other end of list, “rear”
Line of people waiting at bus stop

27. Queue First person in line – first person to board the bus
Automobiles waiting to pass through an intersection – first car in line – first car through

28. Graph
Data contain relationship between pairs of elements which is not hierarchical
E.g., airline flies only between cities connected by lines

29. Data Structure
“record” – files
“node” – linked list, trees and graphs

30. Data Structure Operations
Data structure that one chooses depends on frequency with which specific operations are performed

31. Data Structure Operations
Four operations:
Traversing: Accessing each record exactly once so that items in record may be processed (sometimes called “visiting”)
Searching: Finding location of record with given key value/finding locations of all records which satisfy one/more conditions
Inserting: adding new record
Deleting: removing a record

32. Data Structure Operations
Two/more operations used; e.g., delete record with given key value, mean first need to search for location of record

33. Data Structure Operations
Two operations:
Sorting: arranging records in logical order (e.g., alphabetically according to NAME key/numerical order according to NUMBER key, such as social security/account number)
Merging: combining records in two different sorted files into single