# Explain Algorithm and Flowchart with Examples

##### Flowchart

Algorithms and flowcharts are two different tools used for creating new programs, especially in computer programming. An algorithm is a step-by-step analysis of the process, while a flowchart explains the steps of a program in a graphical way.

### Definition of Algorithm

To write a logical step-by-step method to solve the problem is called algorithm, in other words, an algorithm is a procedure for solving problems. In order to solve a mathematical or computer problem, this is the first step of the procedure. An algorithm includes calculations, reasoning and data processing. Algorithms can be presented by natural languages, pseudo code and flowcharts, etc.

### Definition of Flowchart

A flowchart is the graphical or pictorial representation of an algorithm with the help of different symbols, shapes and arrows in order to demonstrate a process or a program. With algorithms, we can easily understand a program. The main purpose of a flowchart is to analyze different processes. Several standard graphics are applied in a flowchart:

- Terminal Box - Start / End
- Input / Output
- Process / Instruction
- Decision
- Connector / Arrow

The graphics above represent different part of a flowchart. The process in a flowchart can be expressed through boxes and arrows with different sizes and colors. In a flowchart, we can easily highlight a certain element and the relationships between each part.

### Difference between Algorithm and Flowchart

If you compare a flowchart to a movie, then an algorithm is the story of that movie. In other words, an algorithm is the core of a flowchart. Actually, in the field of computer programming, there are many differences between algorithm and flowchart regarding various aspects, such as the accuracy, the way they display, and the way people feel about them. Below is a table illustrating the differences between them in detail.

Algorithm | Flowchart |
---|---|

It is a procedure for solving problems. | It is a graphic representation of a process. |

The process is shown in step-by-step instruction. | The process is shown in block-by-block information diagram. |

It is complex and difficult to understand. | It is intuitive and easy to understand. |

It is convenient to debug errors. | It is hard to debug errors. |

The solution is showcased in natural language. | The solution is showcased in pictorial format. |

It is somewhat easier to solve complex problem. | It is hard to solve complex problem. |

It costs more time to create an algorithm. | It costs less time to create a flowchart. |

### Types of Algorithm

It is not surprising that algorithms are widely used in computer programming. However, it can be applied to solving mathematical problems and even in everyday life. Here come a question: how many types of algorithms? According to Dr. Christoph Koutschan, a computer scientist working at the Research Institute for Symbolic Computation (RISC) in Austria has surveyed about voting for the important types of algorithms. As a result, he has listed 32 important algorithms in computer science. Despite the complexity of algorithms, we can generally divide algorithms into 6 fundamental types based on their function.

Source image: www.educba.com

**1. Recursive Algorithm**

It refers to a way to solve problems by repeatedly breaking down the problem into sub-problems of the same kind. The classic example of using recursive algorithm to solve problems is the Tower of Hanoi.

**2. Divide and Conquer Algorithm**

Traditionally, the divide and conquer algorithm consists of two parts: 1. breaking down a problem into some smaller independent sub-problems of the same type; 2. finding the final solution of the original problems after solving these smaller problems separately.

The key points of the divide and conquer algorithm are:

- If you can find the repeated sub-problems and the loop substructure of the original problem, you may easily turn the original problem into a small simple problem.
- Try to break down the whole solution into various steps (different steps need different solutions) to make the process easier.
- Are sub-problems easy to solve? If not, the original problem may cost lots of time.

**3. Dynamic Programming Algorithm**

Developed by Richard Bellman in the 1950s, the dynamic programming algorithm is generally used for optimization problems. In this type of algorithm, past results are collected for future use. Similar to the divide and conquer algorithm, a dynamic programming algorithm simplifies a complex problem by breaking it down into some simple sub-problems. However, the biggest difference between them is that the latter requires overlapping sub-problems, while the former doesn’t need to.

**4. Greedy Algorithm**

This is another way of solving optimization problems – greedy algorithm. It refers to always finding the best solution in every step instead of considering the overall optimality. That is to say, what he has done is just at a local optimum. Due to the limitations of the greedy algorithm, it has to be noted that the key to choosing a greedy algorithm is whether to consider any consequences in the future.

**5. Brute Force Algorithm**

The brute force algorithm is a simple and straightforward solution to the problem, normally based on the description of the problem and the definition of the concept involved. You can also use "just do it!" to describe the strategy of brute force. In short, a brute force algorithm is considered as one of the simplest algorithms, which iterates all possibilities and ends up with a satisfactory solution.

**6. Backtracking Algorithm**

Based on a depth-first recursive search, the backtracking algorithm focusing on finding the solution to the problem during the enumeration-like searching process. When it cannot satisfy the condition, it will return “backtracking” and tries another path. It is suitable for solving large and complicated problems, which gains the reputation of the “general solution method”. One of the most famous backtracking algorithm example it the eight queens puzzle.

### How to Use Flowcharts to Represent Algorithms

Now that we have the definitions of algorithm and flowchart, how do we use a flowchart to represent an algorithm?

Algorithms are mainly used for mathematical and computer programs, whilst flowcharts can be used to describe all sorts of processes: business, educational, personal and of course algorithms. So flowcharts are often used as a program planning tool to visually organize the step-by-step process of a program. Here are some examples:

**Example 1: Print 1 to 20:**

**Algorithm:**

Step 1: Initialize X as 0,

Step 2: Increment X by 1,

Step 3: Print X,

Step 4: If X is less than 20 then go back to step 2.

**Flowchart:**

**Example 2: Convert Temperature from Fahrenheit (℉) to Celsius (℃)**

**Algorithm:**

Step 1: Read temperature in Fahrenheit,

Step 2: Calculate temperature with formula C=5/9*(F-32),

Step 3: Print C,

**Flowchart:**

**Example 3: Determine Whether A Student Passed the Exam or Not:**

**Algorithm:**

- Step 1: Input grades of 4 courses M1, M2, M3 and M4,
- Step 2: Calculate the average grade with formula "Grade=(M1+M2+M3+M4)/4"
- Step 3: If the average grade is less than 60, print "FAIL", else print "PASS".

**Flowchart:**

### Conclusion

From the above we can come to a conclusion that a flowchart is pictorial representation of an algorithm, an algorithm can be expressed and analyzed through a flowchart.

An algorithm shows you every step of reaching the final solution, while a flowchart shows you how to carry out the process by connecting each step. An algorithm uses mainly words to describe the steps while a flowchart uses the help of symbols, shapes and arrows to make the process more logical.

#### Download Flowchart Software and Use All Symbols and Examples:

How to Create a Fantastic Flowchart

Examples of Algorithm Flowchart