Data Structure Tutorial| Practice & Learn Data Structures Online| Practice Problems

About Data Structure

Programming made simpler, try out Data Structures at TechGig

Things fall into place when your life is organised, programming works in a similar way and to organise data, Data Structures play an important role. Here at TechGig, master the art of organising as well as storing the data and manipulating it according to your code.

TechGig is a "one stop platform" for mastering your basic as well as advanced skills as far as programming is concerned. Data structures are one of the efficient ways to learn any basic programming language. To learn about programming the first step is to ace in Data Structures.

Untangling the complexities of Data Structures

To grasp the advanced concept of programming, data structure is the first step. Data structures are the current trend for many high-level programming languages and some higher level assembly languages too.

Clear your doubts and be a pro with the tutorial TechGig has to offer, all the concepts starting from basic one dimensional array to hashing have sorted approach and illustrative examples motivate your efforts. The basic functioning of the Data Structure is to fetch the data from the machine and store it.

If developing is your main stream then practising Data structures is a must!!! Enjoy this experience of learning and testing yourself with TechGig. Detailed and illustrative path of learning different arrays, linked lists, binary trees, stacks and queue is wonderfully portrayed in TechGig.

Simple approach, coding problems with detailed code and examples is what makes TechGig one of the prominent and best way to gather knowledge for non-coders. Once you have learnt the basic skills, TechGig gives you an opportunity to challenge yourself with different examples, problems and multiple choice questions unless your tend to perfection.

Once you complete this tutorial for Data Structures, your idea of programming has a entirely new dimension and approach, coding is a lot more interesting and stays with you for life. Data Structure is the root to most of the high level programming languages and some of the assembly languages, the tutorials clear basic as well as advanced theories of Data structures.

Learn and test your knowledge on TechGig to help you upgrade your skill set.

Arrays

The collection of similar elements stored in adjoined memory locations is referred to as an array. They are stored in such a way that the position of each element can be easily computed using a basic formula. The position of each element is determined by its offset from the start of the array and therefore the first element is always at position 0 because it has no offset.

Stacks

A stack is a data structure where inserting and deleting items happens at one end from the top of the stack. These stacks access data through the Last In First Out or LIFO approach. Push, pop and display are the three primary operations that can be performed on stacks. Push relates to putting something on the stack, pop takes off something from it and the last operation is for displaying the contents of the stack. One of the example of stack is in UNDO operation where the last operation is undone.

Queue

Queues are an important data structure concept and follow the First In First Out (FIFO) approach to show how it accesses data. While queues are open at both ends, one of the ends is used to insert data or what is known as enqueue, and the other is used to remove data or what is referred to as dequeue. The process in the Computer are scheduled using the queues.

Hashing

Hashing is a technique that helps in converting a range of key values into a range of indexes of an array. It helps maps large amounts of data into smaller tables using the hash function and therefore the efficiency of the mapping activity in hashing would depend on the hash function used. It is the hash function which helps map a given value with a corresponding key for faster access of the elements. For instance, hashing is used in handling (encryption and decryption) digital signatures as it helps in retrieving items quickly from a database.

Heap

A heap denotes a tree-based data structure in which the tree is a complete binary tree and each element is assigned a key value. Heaps are classified into the following two types: Max-Heap structure: In the max-heap structure, the root node has the highest key and the lower value keys always have a parent node with a higher value key. The key present at the root node must be of the highest value among the keys present at all its children. Min-Heap structure: In the min-heap structure, there exists a reverse structure rule where the key present at the root node is of the least value than the keys present at all its children.

Linked List

A linear data structure is dubbed as a Linked List where the elements are not stored at adjoining memory locations. Such a linked list contains of nodes where data fields and reference links are associated with each node and all the elements in the linked list are connected using pointers.

Trees

A binary tree is a form of tree data structure where each node has just two child nodes, referred to as the left child and the right child. In a binary tree, every node will display this attribute of having at most two nodes. Binary tree has the combined benefits of a linked list and an ordered array and as a result insert in binary tree and delete operation in binary tree is quite fast.

Advanced Data Structures

Advanced Data Structure involves the storage and management of complex data in an efficient and organised manner. Doing so, helps in quicker access and modification of data. Tries, Disjoint Sets, Segment Trees, are examples of advanced data structure. Trie, for instance, is an advanced data structure that stores strings consisting of nodes and edges that can be visualized as a graph. Trie derives its name from the reTrieval action and is also called a digital tree. Each node in a Trie representation will consists of different branches consisting of keys. A Trie helps in the alphabetic ordering of the data and information retrieval is typically faster in a Trie data structure.

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