Type of Data Structures

General morphology of data structures is shown in figure 3.

Morphology of Data Structures

















There are two aspects of managing data structures, namely, logical and physical.
A. Logical Data Structures
- Linear Structures
The most common organization for data is a linear structure. A structure is linear if it has these two properties :
Property 1: Each element of the structure is followed by at most one other element
Property 2: No two elements are followed by the same element
An array is an example of a linearly structured data type. We generally write a linearly structured data type like this ABCD.
Counter example 1: If property 1 violates, then BAC, A points to two elements. This example is tree which is non-linear structure. Trees are acyclic structures.



Counter example 2 : If property 2 violates, then ACB, A and B both points to C. This is graph which is again non-linear structure.
Other common linear structure like linked lists, stack & queue are shown above in the picture depicting morphology of the Data Structures.

Non-Linear Structures
In a non-linear structure there is no limit on the number of predecessors or successors of an element of the structure. An element may have a number of successors or predecessor. These structures violate both properties of linear structure. Trees and graphs are the important examples.




A tree is a collection of nodes, where every node has a unique predecessor, but it can have many successors. A Graph is also a collection of nodes. In graph, any node can have any number of successors and predecessors, as shown in figure.