1. Fundamental Concept - Data Structures using C++ by Varsha Patil

1. Oxford University Press © 2012Data Structures Using C++ by Dr Varsha Patil
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2. Oxford University Press © 2012Data Structures Using C++ by Dr Varsha Patil
 Understand the well-defined, clear, and simple approach
of program design
 Learn fundamental aspects of algorithm and its
characteristics
 Learn basic concepts such as data, data type, data
object, data structure, etc.
 Know the power of Abstract Data Type (ADT)
 Study about Software Development Life Cycle (SDLC)
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Program Data
Computer
Output
Fig 1: Processing a Program

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 Machine Language
 Assembly Language
 High-level Language

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 OOP is used to model the real world through objects
 Object-oriented decomposition views software as a set of
well-defined objects that model entities in the application
domain
 These objects interact with each other to form a software
system
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 Data
 Data Type
 Data Object
 Data structure
 Abstract Data Types (ADT)
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 Data is nothing but a piece of information
 Data input, data manipulation (or data processing)
and data output are the themes of computer
 The address of the ith element is calculated by the
following formula
Atomic Data
Composite Data

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 Data type is a term that specifies the type of data that a
variable may hold in the programming language
Built-in Data Types
User Defined Data Types

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 A Data Object represents a container for data values
a place where data values may be stored
and later retrieved
 Data Object is runtime instance of data structure

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 A combination of elements each of which is either a data
type or another data structure and
 A set of associations or relationships (structures)
involving the combined elements
 A data structure is a set of domains D, a designated
domain d Î D, a set of function F, and a set of axioms A
 The triple (D, F, A) denotes the data structure d and it will
usually be written as d
A Data Structure is

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 An Abstract Data Type is a data declaration packaged
together with the operations that are meaningful for the
data type
 Abstract Data Type includes declaration of data,
implementation of operations, and encapsulation of
data and operations

12. Oxford University Press © 2012Data Structures Using C++ by Dr Varsha Patil
 Primitive and Non-Primitive Data Structures
 Linear and Non-linear Data Structures
 Static and Dynamic
 Persistent and Ephemeral Data Structures
 Sequential Access and Direct Access Data Structures
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 A Data Structure is said to be linear if its
elements form a sequence or a linear list
 Linear Data Structure, every data element has
unique successor and unique predecessor

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 In non-linear data structures, every data element
may have more than one predecessor as well as
successor
 Elements do not form any particular linear
sequence

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 Characteristics of Algorithm
 Algorithmic
 Design Tools
 Pseudo Code
 Flow chart

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 The step-by-step solution is called an Algorithm
 Algorithm is independent of computer system and
programming language
 The real world performance of any software depends on two
things
The algorithm chosen, and
The suitability and efficiency of various layers of
implementation

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 Input
 Output
 Unambiguous Steps
 Finiteness
 Effectiveness

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 How to devise algorithms
 How to validate algorithms
 How to analyze algorithms
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 Pseudo code Notations
 Algorithm Header
 Purpose
 Conditions and Return Statement
 Statement Numbers
 Variables
 Statement Constructs
 Sub Algorithms
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 Sequence
 Decision
 Repetition
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Figure 2: Sequence construct

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Figure 3: Decision Construct
If a condition is true,
Then
Else
Algorithm
Purpose :Comparing two numbers
Pre: None
Post: None
Return: None
1) Read two numbers Num1 and Num2
2) If Num1 > Num2
a. Then Print Num1
b. Else Print Num2
3) Stop
Series of Actions
Series of Actions
Example

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Figure 3: Decision Construct
If a condition is true,
Then
Algorithm
Purpose :Comparing two numbers
Pre: None
Post: None
Return: None
1) Read two numbers Num1 and Num2
2) If Num1 > Num2
a. Then Print Num1
b. Else Print Num2
3) Stop
Series of Actions
Series of Actions
Example

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Data Structures in C++ by Dr. Varsha Patil Oxford University Press © 2012
Figure 4: Repetition Construct

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Relationship between Data, Data
Structures, and Algorithms
 A data structure represents a set of data items with
a specific relationship between them.
 The success of a software project often depends
upon the choices made in the representation of
data and algorithms designed to process the data
 The proper choice of a data structure can be a key
point in the design of many algorithms

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 Specification
 Implementation

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 A very effective tool to show the logic flow of a program
 A flow chart is a pictorial representation of an algorithm.
 It hides all of the details of an algorithm by giving the
picture;
 It shows how the algorithm flows from beginning to end

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Figure 5: Flow chart for adding three
numbers

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 Complexity of Algorithms
 Space Complexity
 Time Complexity
 Computing Time Complexity of Algorithm
 Big-O Notation

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 Amount of computer memory required during the
program execution, as a function of the input size
 Space complexity measurement which is space
requirement of an algorithm can be done at two different
times:
 Compile time and
 Execution time

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 Compile Time Space Complexity is defined as the
storage requirement of a program at compile time
 Space Complexity = Space needed of compile time

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 If program is recursive or uses dynamic variables or
dynamic data structure then there is a need to determine
space complexity at runtime
 The memory requirement is summation of the
 Program Space
 Data Space And
 Stack Space

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 Time Complexity of an algorithm is a measure of how
much time is required to execute an algorithm for a given
number of inputs
 Time Complexity T(P) is the time taken by program P
and the sum of the compile and execution time

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 Worst Case
Complexity of the algorithm is the function defined
by the maximum number of steps taken on any instance
of size n
 Best Case
Complexity of the algorithm is the function defined
by the minimum number of steps taken on any instance
of size n
 Average Case
Complexity of the algorithm is the function defined
by an average number of steps taken on any instance of
size n

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 The total time taken by the algorithm or program is
calculated using the sum of the time taken by each of
executable statement in algorithm or program
 Time required by each statement depends on
 Time required for executing it once
 Number of times the statement is executed

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Software Engineering
 Software Engineering is the establishment
and use of sound engineering methods
 and principles to obtain reliable software that
works on real machines
 A fundamental concept in Software
Engineering is the Software Development
Life Cycle (SDLC)

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Software Engineering
 Analysis Phase
 Design Phase
 Implementation Phase
 Testing Phase
 Verification

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Figure 6: System Development Phases
Software Engineering

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Analysis Phase
 Define the User
 Define the Needs
 Define the Requirements
 Define the Methods

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Design Phase
 Modularity
The design phase uses a very well-
established principle called Modularity
The whole package is divided into small
modules

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Implementation Phase
Tools
 Flowchart
 Pseudo Code
 Coding

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Testing Phase
Testing Phase
Once the programs have been written, they must be
tested.
There are two types of testing:
 Black Box
 White Box

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Verification
 Program verification is a process to prove that
the program does what it is intended to do
 It is said that 'even verification must be verified'
 This means, along with system, tests made are
to be verified
 Also, every software quality must be verified

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KEY TERMS
 DATA
 DATA TYPE
 DATA OBJECT
 DATA STRUCTURE
 ABSTRACT DATA TYPE
 LINEAR DATA STRUCUTRE
 NON LINEAR DATA STRUCTURE
 ALGORITHM
 ASSEMBLER
 COMPILER
 PROGRAM
 PSEUDOCODE
 FLOWCHART
 SOFTWARE ENGINEERING

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Summary
 Computer is a programmable data processing machine that accepts
input; instructions to process input (program) and generates
required output. Data and program are stored in computer’s
memory. A program is written in computer’s language.
 The art of programming consists of designing or choosing
algorithms and expressing them in a programming language. An
algorithm is a stepwise description of action which leads the
problem from its start state to its goal state
 One of the common tools used to define algorithms is pseudo code.
Pseudo code is an English-like representation of the code required
for an algorithm. It is part of English, part structured code
 A very effective tool to show the logic flow of a program is the flow
chart. A flow chart is a pictorial representation of an algorithm. It
hides all of the details of an algorithm by giving the picture; it
shows how the algorithm flows from beginning to end
 Program verification is a process to prove that the program does
what it is intended to do

46. Oxford University Press © 2012Data Structures Using C++ by Dr Varsha Patil
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Summary
 Engineering is the establishment and use of sound
engineering methods and principles to obtain reliable
software that works on real machines
 A data structure represents a set of data items with a specific
relationship between them. The success of a software project
often depends upon the choices made in the representation
of data and algorithms designed to process the data. The
proper choice of a data structure can be a key point in the
design of many algorithms

47. Oxford University Press © 2012Data Structures Using C++ by Dr Varsha Patil
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Summary
 The various types Software Engineering is the establishment
and use of sound engineering methodologies and the
principle to writing reliable of data structures are:
 Primitive and Non-primitive data structures
 Linear and Non-linear data structures
 Static and Dynamic data structures
 Persistent and Ephemeral data structures
 Sequential and Direct access data structures

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Summary
 There is an intimate relationship between the structuring of data, and
analysis of algorithms. In fact, a data structure and an algorithm should
be thought of as a one single unit, neither one along making sense
without the other. · Algorithms heavily depend on the organization of
data
 There can be several organizations of data and/or algorithms for a
given problem. Difficulty lies in deciding which algorithms is the best.
We can compare one algorithm with other and choose the best. For
comparison we need to analyze algorithms. Analysis involves
measuring the performance of an algorithm in terms of time and space
complexity

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