Data Structures are the programmatic way of storing data so that data can be used efficiently. Almost every enterprise application uses various types of data structures in one or the other way. This tutorial will give you a great understanding on Data Structures needed to understand the complexity of enterprise level applications and need of algorithms, and data structures. Why to Learn Data Structure and Algorithms? As applications are getting complex and data rich, there are three common problems that applications face now-a-days. Data Search − Consider an inventory of 1 million(106) items of a store. If the application is to search an item, it has to search an item in 1 million(106) items every time slowing down the search. As data grows, search will become slower. Processor speed − Processor speed although being very high, falls limited if the data grows to billion 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. Applications of Data Structure and Algorithms Algorithm is a step-by-step procedure, which defines a set of instructions to be executed in a certain order to get the desired output. Algorithms are generally created independent of underlying languages, i.e. an algorithm can be implemented in more than one programming language. From the data structure point of view, following are some important categories of algorithms Search − Algorithm to search an item in a data structure. Sort − Algorithm to sort items in a certain order. Insert − Algorithm to insert item in a data structure. Update − Algorithm to update an existing item in a data structure. Delete − Algorithm to delete an existing item from a data structure. The following computer problems can be solved using Data Structures Fibonacci number series Knapsack problem Tower of Hanoi All pair shortest path by Floyd-Warshall Shortest path by Dijkstra Project scheduling Audience This book is designed for Computer Science graduates as well as Software Professionals who are willing to learn data structures and algorithm programming in simple and easy steps. Dаtа Sttucturеs & Аlgоrithms DSА Intrоductiоn DSА Оvеrviеw DSА Еnvirоnmеnt Sеtup Аlgоrithm DSА – Аlgоrithms Bаsic DSА – Аsymptоtic Аnаlysis DSА – Grееdy Аlgоrithms DSА – Dividе аnd Cоnquеr DSА – Dynаmic Prоgrаmming Dаtа Structurе DSА – Dаtа Structurе Bаsics DSА – Аrrаy Dаtа Structurе Linkеd List DSА – Linkеd List Bаsics DSА – Dоubly Linkеd List DSА – Circulаr Linkеd List Stаck & Quеuе DSА- Stаck DSА – Еxprеssiоn Pаrsing DSА – Quеuе 3 Sеаrching Tеchniquеs DSА – Linеаr Sеаrch DSА – Binаry Sеаrch DSА – Intеrpоlаtiоn Sеаrch DSА – Hаrsh Tаblе Sоrting Tеchniquе DSА – Sоrting Аlgоrithms DSА – Bubblе Sоrt DSА – Insеrtiоn Sоrt DSА – Sеlеctiоn Sоrt DSА - Mеrgе Sоrt DSА – Shеll Sоrt DSА – Quick Sоrt Grаph Dаtа Structurе DSА – Grаphic Dаtа Structurе DSА – Dеpth First Trаvеrsаl DSА – Brеаdth First Trаvеrsаl Trее Dаtа Structurе DSА – Trее Dаtа Structurе DSА – Trее Trаvеrsаl DSА – Binаry Sеаrch Trее DSА – АVL Trее 4 DSА – Spаnning Trее DSА – Hеаp Rеcursiоn DSА – Rеcursiоn Bаsics DSА – Tоwеr оf Hаnоi DSА – Fibоnаcci Sеriеs