1) The document discusses data structures and their importance for organizing data, designing large computer systems, and writing efficient programs. 2) It covers common data structures like arrays, stacks, queues, linked lists, trees and graphs. Choosing the right data structure depends on the problem and constraints like space and time. 3) Analyzing algorithms' worst, average, and best cases helps determine efficiency. Practicing with examples like sorting numbers and searching databases improves skills with data structures.

1. Thinking in Data Structures
Tushar B Kute
http://www.tusharkute.com

2. Data Structure
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What is the "Data Structure" ?
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Ways to represent data.
In a general sense, any data representation is a data structure.
Example: An integer more typically, a data structure is meant to be
an organization for a collection of data items.
Why data structure ?
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Have proven correct algorithms
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To design and implement large-scale computer system
The art of programming
How to master in data structure ?
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practice, discuss, and think
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3. Need of data structures
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Data structures organize data
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More powerful computers
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More efficient programs.
More complex applications.
More complex applications demand more calculations.
Complex computing tasks are unlike our everyday
experience.
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4. List of data structures
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Static
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Stack
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Array
Queue
Dynamic
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Linked list
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Tree
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Graph
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5. Choosing a data structure
int p[10], i=0;
int *p, i=0;
while(1)
while(1)
{
{
scanf(“%d”, &p[i]);
i++;
}
scanf(“%d”, &p[i]);
i++;
}
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6. System life cycle
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Summary
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Requirements
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RADRCV
What inputs, functions, and outputs.
Analysis
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Break the problem down into manageable pieces.
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Top-down approach.
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Bottom-up approach.
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7. System life cycle
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Design
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Refinement and Coding
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Create abstract data types and the algorithm
specifications, language independent.
Determining data structures and algorithms.
Verification
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Developing correctness proofs, testing the program,
and removing errors.
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8. Efficiency
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A solution is said to be efficient if it solves the problem
within its resource constraints.
–
–
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Space
Time
The cost of a solution is the amount of resources that the
solution consumes.
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9. Data Structure philosophy
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Each data structure has costs and benefits.
Rarely is one data structure better than another in all
situations.
A data structure requires:
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–
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space for each data item it stores,
time to perform each basic operation,
Programming effort.
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10. Data structure philosophy
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Each problem has constraints on available space and
time.
Only after a careful analysis of problem characteristics
can we know the best data structure for the task.
Bank example:
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Start account: a few minutes
–
Transactions: a few seconds
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Close account: overnight
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11. Example.
for(a=0; a>10; a++)
//loop-1
{
printf(“Hello World...”);
}
for(a=0; a<10; a++)
//loop-2
{
printf(“Hello World...”);
}
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12. Example.
for(a=0; a<=10; a++)
//loop-3
{
printf(“Hello World...”);
}
for(a=0; a!=10; a++)
//loop-4
{
printf(“Hello World...”);
}
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13. Example: check for prime number
flag=0;
for(a=2;a<num;a++)
{
if(num%a==0)
flag=1;
}
if(flag==1)
printf(“Number is not prime.”);
else
printf(“Number is prime.”);
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14. Refinement-1
flag=0;
for(a=2;a<num;a++)
{
if(num%a==0) {
flag=1;
break;
}
}
if(flag==1)
printf(“Number is not prime.”);
else
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printf(“Number is prime.”);
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15. Refinement-2
flag=0;
for(a=2;a<num/2;a++)
{
if(num%a==0) {
flag=1;
break;
}
}
if(flag==1)
printf(“Number is not prime.”);
else
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printf(“Number is prime.”);
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16. Refinement-3
for(a=2;a<num/2;a++)
{
if(num%a==0)
break;
}
if(a==(num/2))
printf(“Number is prime.”);
else
printf(“Number is not prime.”);
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17. Example: swapping of two numbers, Way-1
a=13, b=29;
temp = a;
a = b;
b = temp;
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18. Way-2
a=13, b=29;
a = a + b;
a = a – b;
b = a – b;
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19. Way-3
a=13, b=29;
a = a ^ b;
b = a ^ b;
a = a ^ b;
or
a^=b^=a^=b;
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20. Worst / Average / Best case
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Worst-case running time of an algorithm
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The longest running time for any input of size n
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An upper bound on the running time for any input
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Guarantee that the algorithm will never take longer
Example: Sort a set of numbers in increasing order; and the data is in
decreasing order
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The worst case can occur fairly often
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E.g. in searching a database for a particular piece of information
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Best-case running time
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Sort a set of numbers in increasing order; and the data is already in
increasing order
Average-case running time
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May be difficult to define what “average” means
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21. Example: searching in database
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Best case: O(1)
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Worst case: O(n)
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Average case: O(n/2)
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22. Running time of algorithms
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Bounds are for the algorithms, rather than programs
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Programs are just implementations of an algorithm,
and almost always the details of the program do not
affect the bounds
Bounds are for algorithms, rather than problems
–
A problem can be solved with several algorithms,
some are more efficient than others
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23. Describing algorithms
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Natural language
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English, Chinese
Instructions must be definite and effectiveness.
Graphic representation
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Flowchart
Work well only if the algorithm is small and simple.
Pseudo language
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Readable
Instructions must be definite and effectiveness.
Combining English and C
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Simple and Tough task to do.
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24. Algorithm and programs
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Algorithm: a method or a process followed to solve a
problem.
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An algorithm takes the input to a problem (function) and
transforms it to the output.
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A recipe: The algorithm gives us a “recipe” for solving
the problem by performing a series of steps, where
each step is completely understood.
A mapping of input to output.
A problem can be solved by many algorithms.
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25. A problem can have many solutions
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For example, the problem of sorting can be solved by the
following algorithms:
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Insertion sort
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Bubble sort
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Selection sort
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Shell sort
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Merge sort
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Radix sort
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Merge sort
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Quick sort
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26. Algorithm properties
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An algorithm possesses the following properties:
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It must be composed of a series of concrete steps.
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There can be no ambiguity as to which step will be
performed next.
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It must be composed of a finite number of steps.
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It must be correct.
It must terminate.
A computer program is an instance, or concrete
representation, for an algorithm in some programming
language.
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27. Thank you
This presentation is created using LibreOffice Impress 3.6.2.2
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