- DSA - Discussion
- DSA - Useful Resources
- DSA - Quick Guide
- DSA - Questions and Answers
- DSA - Fibonacci Series
- DSA - Tower of Hanoi
- DSA - Recursion Basics
- DSA - Heap
- DSA - Tries
- DSA - Spanning Tree
- DSA - Splay Trees
- DSA - B+ Trees
- DSA - B Trees
- DSA - Red Black Trees
- DSA - AVL Tree
- DSA - Binary Search Tree
- DSA - Tree Traversal
- DSA - Tree Data Structure
- DSA - Breadth First Traversal
- DSA - Depth First Traversal
- DSA - Graph Data Structure
- DSA - Quick Sort
- DSA - Shell Sort
- DSA - Merge Sort
- DSA - Selection Sort
- DSA - Insertion Sort
- DSA - Bubble Sort
- DSA - Sorting Algorithms
- DSA - Hash Table
- DSA - Interpolation Search
- DSA - Binary Search
- DSA - Linear Search
- DSA - Queue
- DSA - Expression Parsing
- DSA - Stack
- DSA - Circular Linked List
- DSA - Doubly Linked List
- DSA - Linked List Basics
- DSA - Array Data Structure
- DSA - Data Structures and Types
- DSA - Data Structure Basics
- DSA - Dynamic Programming
- DSA - Divide and Conquer
- DSA - Greedy Algorithms
- DSA - Asymptotic Analysis
- DSA - Algorithms Basics
- DSA - Environment Setup
- DSA - Overview
- DSA - Home
Selected Reading
- Who is Who
- Computer Glossary
- HR Interview Questions
- Effective Resume Writing
- Questions and Answers
- UPSC IAS Exams Notes
Data Structures & Algorithms - Overview
Data Structure is a systematic way to organize data in order to use it efficiently. Following terms are the foundation terms of a data structure.
Interface − Each data structure has an interface. Interface represents the set of operations that a data structure supports. An interface only provides the pst of supported operations, type of parameters they can accept and return type of these operations.
Implementation − Implementation provides the internal representation of a data structure. Implementation also provides the definition of the algorithms used in the operations of the data structure.
Characteristics of a Data Structure
Correctness − Data structure implementation should implement its interface correctly.
Time Complexity − Running time or the execution time of operations of data structure must be as small as possible.
Space Complexity − Memory usage of a data structure operation should be as pttle as possible.
Need for Data Structure
As apppcations are getting complex and data rich, there are three common problems that apppcations face now-a-days.
Data Search − Consider an inventory of 1 milpon(106) items of a store. If the apppcation is to search an item, it has to search an item in 1 milpon(106) items every time slowing down the search. As data grows, search will become slower.
Processor speed − Processor speed although being very high, falls pmited if the data grows to bilpon records.
Multiple requests − As thousands of users can search data simultaneously on a web server, even the fast server fails while searching the data.
To solve the above-mentioned problems, data structures come to rescue. Data can be organized in a data structure in such a way that all items may not be required to be searched, and the required data can be searched almost instantly.
Execution Time Cases
There are three cases which are usually used to compare various data structure s execution time in a relative manner.
Worst Case − This is the scenario where a particular data structure operation takes maximum time it can take. If an operation s worst case time is ƒ(n) then this operation will not take more than ƒ(n) time where ƒ(n) represents function of n.
Average Case − This is the scenario depicting the average execution time of an operation of a data structure. If an operation takes ƒ(n) time in execution, then m operations will take mƒ(n) time.
Best Case − This is the scenario depicting the least possible execution time of an operation of a data structure. If an operation takes ƒ(n) time in execution, then the actual operation may take time as the random number which would be maximum as ƒ(n).
Basic Terminology
Data − Data are values or set of values.
Data Item − Data item refers to single unit of values.
Group Items − Data items that are spanided into sub items are called as Group Items.
Elementary Items − Data items that cannot be spanided are called as Elementary Items.
Attribute and Entity − An entity is that which contains certain attributes or properties, which may be assigned values.
Entity Set − Entities of similar attributes form an entity set.
Field − Field is a single elementary unit of information representing an attribute of an entity.
Record − Record is a collection of field values of a given entity.
File − File is a collection of records of the entities in a given entity set.