Some Important Linear Data Structures at a glance To go through the C program / sourcecode, scroll down to the end of this pageCircular linked list is a more complicated linked data structure. In this the elements can be placed anywhere in the heap memory unlike array which uses contiguous locations. Nodes in a linked list are linked together using a next field, which stores the address of the next node in the next field of the previous node i.e. each node of the list refers to its successor and the last node points back to the first node unlike singly linked list. It has a dynamic size, which can be determined only at run time. Related Tutorials :
Performance1. The advantage is that we no longer need both a head and tail variable to keep track of the list. Even if only a single variable is used, both the first and the last list elements can be found in constant time. Also, for implementing queues we will only need one pointer namely tail, to locate both head and tail. 2. The disadvantage is that the algorithms have become more complicated. Basic Operations on a Circular Linked ListInsert – Inserts a new element at the end of the list. Delete – Deletes any node from the list. Find – Finds any node in the list. Print – Prints the list. Complete tutorial with examples (Source code and MCQ Quiz below this)Circular Linked List  C Program source code#include<stdio.h>
Related Visualizations (Java Applet Visualizations for different kinds of Linked Lists) :Lists : Linear data structures, contain elements, each of
which point to the "next" in the sequence as demonstrated in the
examples below ( Simple, Circular and Double Linked Lists are some
common kinds of lists ) . Additions and removals can be made at any
point in the list  in this way it differs from stacks and queues.
1. Simple Linked Lists  A Java Applet Visualization

Arrays : Popular Sorting and Searching Algorithms 
 
Selection Sort  Shell Sort  
Heap Sort  Binary Search Algorithm  
Basic Data Structures and Operations on them  
Single Linked List  Double Linked List  
Tree Data Structures  
Binary Search Trees  Heaps  Height Balanced Trees  
Graphs and Graph Algorithms  
Depth First Search  Breadth First Search  Minimum Spanning Trees: Kruskal Algorithm  Minumum Spanning Trees: Prim's Algorithm 
Dijkstra Algorithm for Shortest Paths  Floyd Warshall Algorithm for Shortest Paths  Bellman Ford Algorithm  
Popular Algorithms in Dynamic Programming  
Dynamic Programming  Integer Knapsack problem  Matrix Chain Multiplication  Longest Common Subsequence 
Greedy Algorithms  
Elementary cases : Fractional Knapsack Problem, Task Scheduling  Data Compression using Huffman Trees 