- INTRODUCTION TO DS
- ALGORITHMS
- ASYMPTOTIC ANALYSIS
- DYNAMIC PROGRAMMING
- DIVIDE AND CONQUER
- Arrays
- Linked List
- STACK
- EXPRESSION PARSING
- Queue
- GRAPHS
- TREE
- SEARCHING TECHNIQUES
- Binary Search
- Indexed Sequential Search
- Breadth First Search
- Depth First Search
- Interpolation Search
- Complexity
- Binary Search
- Indexed Sequential Search
- Breadth First Search
- Depth First Search
- Interpolation Search
- Complexity
- Binary Search
- Indexed Sequential Search
- Breadth First Search
- Depth First Search
- Interpolation Search
- Complexity
- Binary Search
- Indexed Sequential Search
- Breadth First Search
- Depth First Search
- Interpolation Search
- Complexity
- Binary Search
- Indexed Sequential Search
- Breadth First Search
- Depth First Search
- Interpolation Search
- Complexity
- Binary Search
- Indexed Sequential Search
- Breadth First Search
- Depth First Search
- Interpolation Search
- Complexity
- SORTING
- Bubble Sort
- Selection Sort
- Quick Sort
- Insertion Sort
- Radix Sort
- Merge Sort
- Shell Sort
- Heap Sort
- Complexity
- Bubble Sort
- Selection Sort
- Quick Sort
- Insertion Sort
- Radix Sort
- Merge Sort
- Shell Sort
- Heap Sort
- Complexity
- Bubble Sort
- Selection Sort
- Quick Sort
- Insertion Sort
- Radix Sort
- Merge Sort
- Shell Sort
- Heap Sort
- Complexity
- Bubble Sort
- Selection Sort
- Quick Sort
- Insertion Sort
- Radix Sort
- Merge Sort
- Shell Sort
- Heap Sort
- Complexity
- Bubble Sort
- Selection Sort
- Quick Sort
- Insertion Sort
- Radix Sort
- Merge Sort
- Shell Sort
- Heap Sort
- Complexity
- Bubble Sort
- Selection Sort
- Quick Sort
- Insertion Sort
- Radix Sort
- Merge Sort
- Shell Sort
- Heap Sort
- Complexity
- Bubble Sort
- Selection Sort
- Quick Sort
- Insertion Sort
- Radix Sort
- Merge Sort
- Shell Sort
- Heap Sort
- Complexity
- Bubble Sort
- Selection Sort
- Quick Sort
- Insertion Sort
- Radix Sort
- Merge Sort
- Shell Sort
- Heap Sort
- Complexity
- Bubble Sort
- Selection Sort
- Quick Sort
- Insertion Sort
- Radix Sort
- Merge Sort
- Shell Sort
- Heap Sort
- Complexity
- Recursion
- Backtracking
- Hashing
INTRODUCTION TO DS
Data Structures are the programmatic way for storing Data for using the data in an efficient manner. It is the branch of Computer Science that unleashes the knowledge of how the data should be organized, how the flow of data should be controlled and how a data structure should be designed and implemented to reduce the complexity and increase the efficiency of algorithm. The study of Data structures used for analyzing algorithms has continued.
The study of Data structure can be categorized in to steps.
1.The first is to identify the problem and find that these can be solved by using which entities and operations.
2.The second is to determine the representation of these entities and implementation of operations on these representations.
The theory of Data structures not only introduces you to the data structures, but also helps you to understand and use the concept of abstraction, analyze the problem step by step and develop algorithms to solve real world problems. It enables you to design and implement various data structures, for e.g.
The stacks, queues, linked lists, trees and graphs.
Effective use of Data structures increases efficiency of algorithms to solve problems like searching, sorting and handling voluminous data.
Data structure mainly specify following things.
- Organization of data.
- Accessing of associativity.
- Degree of Associativity.
- Processing alternative for information.