Introduction To Data Structure > Basic Concepts > What is data structure? > What is Algorithm? > Examples > 1D & 2D array representation in memory

1. Elementary of
Data Structure &
Algorithms
B. MANDAL

2. Basic Terminology
A good program is that
 Runs correctly
 Easy to read & understand
 Easy to debug
 Easy to modify
A program should undoubtedly
 Gives correct result &
 Efficiently
To write efficient programs – we need to
enforce certain data management concepts

3.  A group of data elements that put together under one
name.
 Data Structure is a way of storing and organizing
data in computer system.
 Logically &
 Mathematically
 Purpose :– For efficient access of stored data
Data Structure

4.  Data: a value or set of values
 Record: collection of data items
 E.g. name, address & subject for a particular student
 File: collection of related records [Dictionary]
 Key: one or more data item(s) which will uniquely
identify each records form a file.
Data Structure – Elementary

5.  Primitive: atomic, fundamental data types (e.g. integer,
real, Boolean)
 Non-primitive: derived from primitive DS (e.g. array,
structure)
 Linear: elements are stored in linear or sequential manner.
 Linear memory allocations
 Linear relationship between elements
 E.g. Array, linked list, Stack, Queue …
 Non-Linear: elements are not stored in linear manner.
 E.g. Graph, Tree
Classification of Data Structure

6.  Traversing: Accessing each data item exactly once
 Searching: Finding location of one/more data items
 Inserting: Add new data items
 Deleting: Removing data
 Sorting: Arranging data
 Merging: Combining set of data
Operations on Data Structure

7.  Way we look at a Data Structure
 Focusing on what it dose
 Ignoring implementation details
 E.g. List, Stack, Queue …
 Real world problem solving
Abstract Data Type (ADT)

8.  Any well-defined computational procedure
 Takes some value, or set of values, as input
 produces some value, or set of values, as output
An algorithm is a sequence of computational steps that
transform the input into the output.
 For a particular problem – we may have several
algorithms
 One algorithm may not fit for other problems
Algorithm

9.  Ex. Searching an element from a list
Algo: Search(A, key, N)
{
For i=0 to N
if( A[i] == key )
RETURN (i)
RETURN (-1)
}

10.  Ex. GCD of two number
Al go rith m: G CD(a, b)
{
wh il e (a ≠ b)
{
if a > b
a ← a – b
el se
b ← b – a
}
R ETU R N (a)
}

11.  Ex. Factorial of positive integer
Algorithm: Factorial(n)
{
Fact ← 1
If n = 1
return (1)
else
Fact ← n * Factorial(n - 1)
return (Fact)
}

12.  Collection of similar data item
 Referred by a common name
 Contiguous memory allocation
 E.g. int Student[10];
Array

13. 2-Dimentional Array
 E.g. char matrix[5] [4];


14.  E.g. char matrix[6] [12];
 Will not fit


15.  2-dimensional array mapped to 1-dimensional array
 Special way to access
 E.g.
char A[3][4];
A ⇒ 0 1 2 3
0
1
2
A´ ⇒
Representation in Memory
a b c d
e f g h
i j k l
a b c d e f g h i j k l
0 1 2 3 4 5 6 7 8 9 10 11
A [row][col] = A´ [row * m + col]
m  # columns

16. Dynamic Memory Allocation
 Calloc – contiguous memory allocation
 Arr = (int *) calloc(n, sizeof(int))
 Malloc – block of memory allocation
 Arr = (int *) malloc(n * sizeof(int))
 Free: release memory
 free(Arr)
 **Arr is a pointer to integer

17. Thank You 