1. Data Structures
Arvind Devaraj

2. Data Structure Selection
• What data structure will you use in the
following Scenarios

3. Ten people are standing
in a row.
Every third person is
eliminated.
Which person remains
Which Data structure ? Array, List, Tree, Stack, Queue ?????
SCENARIO-1

4. SCENARIO 2
Recent 5 missed
calls must be
displayed
Which Data structure ? Array, List, Tree, Stack, Queue ?????

5. SCENARIO 3
• Need to maintain database of student
names…support for
– Insert, Delete, Search
– (also) next and previous person
– (also) find who got maximum marks
Which Data structure ? Array, List, Tree, Stack, Queue ?????

6. SCENARIO 4
Each person is assigned a priority number
when he enters an office. The person who
has the highest priority is served
Each process is having priority. The OS
schedules the one having the highest
priority
Which Data structure ? Array, List, Tree, Stack, Queue ?????

7. Arrays (vs List)
+ Fast Access
+ Memory consumption is minimal
- Insertion and deletion is complicated

8. Linked Lists
• A way of making variable length arrays
– In which insertions and deletions are easy
• But nothing comes for free
– Finding an element can be slow
– Extra space is needed for the links

9. Linked List Example
Jill Joe Tom
first
Public static main (String[] argv) {
Student first;
…
}
Public class Student {
String name;
public Student next;
}

10. Trees
• Linked list with multiple next elements
Binary trees are useful for relationships like “<“ ,
“>”
• Insertions and deletions are easy
• Useful for fast searching of large
collections

11. Binary Tree Example
Jill
Joe
Tom
root Public class Student {
int String name;
public Student left;
public Student right;
}

12. Write a program
• height of binary tree
• Count leaves
• Find minimum value
• Locate a particular node
• Find successor of a node
• Check if it’s a Binary Search tree

14. int height( BinaryTree Node t)
{
if t is a null tree
return -1;
hl = height( left subtree of t);
hr = height( right subtree of t);
h = 1 + maximum of hl and hr;
return h;
}

15. Hashtables
• Find an element nearly as fast as in an
array
– With easy insertion and deletion
– But without the ability to keep things in order
• Fairly complex to implement
– But Java defines a class to make it simple
• Helpful to understand how it works
– “One size fits all” approaches are inefficient

16. Choosing a Data Structure
• What operations do you need to perform?
• Hashing finds single elements quickly
– But cannot preserve order
• Stacks and linked lists preserve order easily
– But they can only read one element at any time
• Balanced trees are best when you need both
– Need to read in blocks (for disks)
– B-Tree is used