What is an Algorithm: Definition, Types, Characteristics

The complex nature of various algorithms is the reason why most of the tech giants include them in assessing their talent pools, be it Google, Meta, or Amazon. The tech talent has to go through an assessment that includes a rigorous round consisting of algorithms. Hence, to implement algorithms, it’s important to understand its meaning, needs, and how it works. In this blog, we have curated all the essential details about algorithms to help you understand their implementation properly. 

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What is an Algorithm?

An algorithm is a methodical approach that contains a set of guidelines or rules to solve a problem or carry out a technical task. Once the algorithms are written, it can be converted into programs using programming languages like C, C++, Python, etc.

Let’s understand this with the help of an example: 

Let’s say you want to make some tea. To do this successfully, you need to follow certain steps in a particular order. Firstly, you will boil the water in a saucepan, then eventually you will add sugar and tea powder and boil it for 3-4 minutes. Then you will add some milk to it and boil it for 6-7 minutes; eventually, you will see the color change to brown. Lastly, strain the tea into a cup and serve it.

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How Do Algorithms Work?

Algorithms process the inputs, and get through a series of steps or guidelines or rules to produce an output or outcome. 

Taking the context of the above example, if you are trying to make tea, the ingredients are the inputs, the recipe is the rule, and the end product, i.e., tea, is the outcome or output.

This can be better understood with the help of the following diagram:

Now let’s take a real-world program wherein we have to write an algorithm that finds the square of a number. Here, the number that is given as an input, let say x, is the input to the algorithm. Then there are some steps that will be executed to find the square of the number and finally you will get the square of the number x.

Here is how you represent the algorithm:

Step 1: Start

Step 2: Declare a variable x, square (to store the output)

Step 3: square = x*x

Step 4: Display square

What Is the Need for Algorithms?

You will require an algorithm for the following reasons:

• Optimizes Problem-solving: An algorithm helps us grasp the fundamental concept of the problem solving as it written in simple English and follows a step-by-step approach to solve a problem statement.
• Measure of Performance: Algorithms are the best way to measure the performance of the program in all cases, time complexity, space complexity (best cases, worst cases, average cases).
• Resource Allocation: Algorithms are used to determine the best possible way to solve a problem statement based on the amount of resources used in terms of storage and processing power. So writing an algorithm can help us determine the resources required to run the algorithm and accordingly resource allocation can be done.

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How to Write an Algorithm?

An algorithm can be expressed in three different ways. They are:

1. Natural Language: An algorithm can be expressed in a natural language like English. But it is usually hard to understand and is not the best way to express an algorithm.
2. Flow Charts: Flow charts are another way of expressing an algorithm where we make use of diagrams to represent the algorithm.
3. Pseudo-Code: It is the best way to express an algorithm. In pseudo-code,  we explain the algorithm in steps. It doesn’t have any syntax like any other programming language. Therefore,  it can’t be interpreted or compiled. The previously mentioned example of Making Tea is a Pseudocode way to express an algorithm.

Also, check out our blog on the Key Difference Between Algorithm and Flowcharts!

Examples of Algorithms

1. Algorithm 01: Factorial of a number

Step 1: Start

Step 2: Declare variables n, factorial, and i.

Step 3: Initialize variables

          factorial ← 1

          i ← 1

Step 4: Read the value of n

Step 5: Repeat the steps until i = n

     5.1: factorial ← factorial*i

     5.2: i ← i+1

Step 6: Display factorial

Step 7: Stop

2. Algorithm 02: Check if a number is a Prime number or not

Step 1: Start

Step 2: Declare variables n, i, flag.

Step 3: Initialize variables

        flag ← 1

        i ← 2  

Step 4: Read n from the user.

Step 5: Repeat the steps until i=(n/2)

     5.1 If the remainder of n÷i equals 0

            flag ← 0

            Go to step 6

     5.2 i ← i+1

Step 6: If flag = 0

           Display n is not prime

        else

           Display n is prime

Step 7: Stop

3. Algorithm 03: Fibonacci Series

Step 1: Start 

Step 2: Declare variables first_term,second_term and temp. 

Step 3: Initialize variables first_term ← 0 second_term ← 1 

Step 4: Display first_term and second_term 

Step 5: Repeat the steps until second_term ≤ 1000 

     5.1: temp ← second_term 

     5.2: second_term ← second_term + first_term 

     5.3: first_term ← temp 

     5.4: Display second_term 

Step 6: Stop

Types of Algorithm

1. Brute Force Algorithm

• Brute force algorithms are simple and straightforward solutions that use trial and error to solve problems.
• They are often used to solve problems where no other efficient solution is known. Although they can be very slow, they are easy to understand and implement.

2. Divide and Conquer Algorithm

• Divide and conquer algorithms break a complex problem into smaller, simpler sub-problems. The sub-problems are then solved separately and combined to solve the original problem.
• This approach reduces the complexity of the problem and makes it easier to solve.

3. Dynamic Programming Algorithm

• Dynamic programming algorithms are used to solve problems that can be broken down into smaller sub-problems.
• They use a bottom-up approach, starting with the simplest sub-problems and building up to the more complex ones.
• This approach is used to find the optimal solution to a problem by avoiding redundant calculations.

4. Greedy Algorithm

• Optimization issues are resolved using greedy algorithms. They always choose well and never turn around.
• This strategy is utilized when the answer may be discovered by making a sequence of local optimal decisions that ultimately result in a globally optimal solution.

5. Backtracking Algorithm

• Backtracking algorithms are used to solve problems that involve finding a solution by trying different options and undoing them if they lead to a dead end.
• This approach is used when there is no efficient way to solve the problem and it is necessary to try all possible solutions.

Time and Space Complexity

An algorithm can be defined as efficient based on the time and space it consumes while we execute the program. The more time and space it takes, the less efficient it is.

1. Space Complexity: 

The space complexity of an algorithm is defined as the amount of memory required to store the variables, inputs, and output of the algorithm. The smaller the space, the better the algorithm.

2. Time Complexity: 

The time complexity of an algorithm is defined as the amount of time taken to execute the algorithm and produce the output. The less time, the better the algorithm.

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Factors of an Algorithm

Following are the factors to be considered while designing an algorithm:

• Modularity: An algorithm can be defined as modular if it can be broken down into smaller modules for the problem statements.
• Correctness: The correctness of an algorithm is defined by the output one receives concerning the input given to the algorithm.
• Simplicity: The simplicity of an algorithm is defined if it is the algorithm is easy to understand.
• Maintainability: The maintainability of an algorithm is defined when there is a need to revamp the algorithm without major changes. 
• User-friendly: An algorithm is said to be user-friendly if the designer can easily explain the algorithm to the programmer.
• Functionality: The algorithm is said to be functional if it has all the functionalities to solve the problem statement. 
• Extensibility: An algorithm is said to be extensible if new functionality can be added to the algorithm without modifying the code.
• Robustness: The robustness of an algorithm can be defined as per its ability to define the problem clearly.

Qualities of a Good Algorithm

The following are the qualities of a good algorithm:

1. Time: An algorithm is better if it takes less time to execute,i.e, less time complexity.
2. Space: An algorithm is better if it takes less or no space to execute, i.e., less space complexity.
3. Accuracy: An algorithm is better if it provides accurate results for the problem statement.

Advantages of Algorithm

1. Streamlines Problem Solving: Algorithms give us a standardized and clear step-by-step process for solving a problem statement, hence streamlining problem solving.
2. Improves Efficiency: An algorithm can be broken down into smaller modules. Therefore, it’s easier for the coder to write good quality code.
3. Enables Reusability: An algorithm can be reused in different projects, therefore saving time and effort for the development team.

Related Reading

1. Data Structures
2. Arrays
3. Stacks and Queues
4. Linked Lists
5. Tree Data Structure
6. Graphs Data Structure
7. Sorting Algorithms
8. Searching Algorithms
9. DSA Interview Questions and Answers

Conclusion

I hope this blog has been a great help to you in understanding algorithms. Best of luck!

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