Algorithms and Data Structures

Algorithms are the backbone of computing. Without the knowledge of algorithms, computing would have had major setbacks.

So what then is an algorithm?

An algorithm is a definite sequence of instruction logically written in an order that accomplishes a predefined task.

You should understand that an algorithm does not mean it is the whole code of the program. It only represents a section that solves a specific problem in a program. This can be shown using a flowchart, pseudocodes or high-level description.

The following are conditions that all algorithms should meet:

• Input- there should be zero (0) or more externally supplied inputs to the algorithm.
• Output- one or more outputs should be expected from the algorithm.
• Finiteness- the steps of the algorithm should be finite.
• Definiteness- all steps of an algorithm should be defined and clear.
• Correctness- the steps in the algorithm should give an expected result.

You need to strive to make your algorithm fast and efficient. If an algorithm achieves its result within the shortest time, it is termed an efficient algorithm. Another point to note is that fast and efficient algorithms don’t consume much space.

The factors used to measure the performance of any algorithm is the:

• Time Complexity
• Space Complexity

Data Structure

Data Structure is practically a method of obtaining and organizing data in ways that you can use to perform operations. The aim of Data Structures is to arrange data elements, create relationships between the elements in order to get efficient organization and low storage.

Basic forms of Data Structures

Good examples of simple data structures are:

• Integer
• Float
• Boolean
• Char

These are all called data structures. Although they are commonly referred to as Primitive Data Structures.

When it comes to storing a large amount of data and having large interconnected data, then a more complex Data Structure will come to play.

The data structure is designed to speed up different operations on data. The choice of the data structure to choose from is determined majorly by the type of operation that is needed.

2 Classical Categories of Data Structure

You will find two subdivisions of data structure, these are:

• Linear Data Structure
• Non-linear Data Structure

Linear data structures are formed by combining elements to form a specific order. You have two easy options to use when you want to represent data using the linear structure within memory.

Option one: you need to get the linear relationships among the elements represented with the use of linear memory location. This kind of linear structure is usually referred to as an array.

Option two: you need to get a linear relationship among the elements represented with the use of the concept of links or pointers. This kind of linear structure is referred to as a linked list.

The non-linear data structure on the other hand usually used to represent data that is having a hierarchical relationship among various elements.

The following are typical of non-linear data structures are:

• Graph
• The family of trees.
• Table of contents.

Reasons to learn Algorithms and Data Structure

If you want to become a sound application developer, you need to understand a lot about algorithms and data structure.

If you plan to work with established companies, then learning algorithms and data structure is a must.