How To Solve Programming Problems

Programming is an art. It’s not just about writing code. It’s about problem-solving. Becoming a better programmer can help you solve both kinds of problems better, and help your organization be more effective at what it does. To do that, you’ll need to develop new skills beyond those needed to write code and understand some of the culture of programming as well as the ideas behind it.

What Is Computational Thinking?

Computational thinking is a mindset and a skillset that lets you take apart and put together systems in new ways, to achieve what you want. It’s not just about coding. But the ability to use computers and other tools is important.

Computational thinking at its most basic, it’s the idea that you can use your brain to solve problems. Computational thinking involves things like comparing and contrasting ideas; looking for commonalities between seemingly different concepts; using data to make decisions; creating simulations of real-world phenomena; searching for patterns in large data sets. It’s not just about computers. Computational thinking gives students a way to think with many kinds of content.

How To Solve Programming Problems Using Computational Thinking?

Writing code is not the first step to build a software or a program. There are some steps before putting your hands on the keyboard. these steps are:

  • Problem Decomposition.
  • Pattern Recognition.
  • Abstract Thinking.
  • Algorithmic Thinking.
  • Debugging And Testing.

Problem Decomposition

The problem decomposition method is a type of bottom-up approach to solving complex problems. In this method, the problem is divided into as many smaller sub-problems as possible, with each sub-problem being broken down again if necessary until it is small enough to solve easily.

To analyze a problem, you can use IPO model:

  • I (Input) = They are the things that you have to feed your program with. it can be user text or numbers, files, or anything that is external. these inputs help to produce results using your program. They can be one or multiple inputs.
  • P (Process) = It can be functions, mathimatical operations, and so on. You can have one function or two or more. These functions works with inputs in order to produce the outcome that we need.
  • O (Output) = This is the results that we want to achieve with our program.

In some cases, it can be only process without inputs but it must be an output.

For example:

  • Input: Number A, Number B
  • Process: Addition function (sumNumbers = Number A + Number B)
  • Output: The results of the addition function (sumNumbers)

This is a basic example. programs work like that and to decompose your program, you need to think what the results I want, what input I need to produce this result, and what process I need to do to achieve my goal.

You have to break down your program into smaller parts and do IPO model for every part you have.

Pattern Recognition

Pattern recognition is the ability to notice meaningful patterns in data. As you can imagine, it’s involved in many different fields like computer vision, biology, psychology, physics, and mathematics.

Pattern recognition is a fundamental skill that humans learn to perform at an early age. The human brain has the ability to recognize common patterns in information and make predictions based on those patterns.

You have to think of problems that you have solved in the past that are similar to your current problem or the problem that you solved in the same current problem because that solution will be similar to the one that you are looking for. you just need to include it and change it a little if you need.

Abstract Thinking

Abstract thinking is the ability to see beyond the concrete and focus on what is essential. It’s a way of analyzing and describing something without getting distracted by details.

Abstractions are the most important part of computational thinking. Abstraction allows us to solve problems in a generic way, by reducing them to simpler or more fundamental concepts. This can be done by imagining that you are working with a simplified version of the problem that only has some of the properties of the original problem.

In your problem, you have to ignore some details and things that you don’t need at the moment. focus just on things that will help you solve your current subproblem and not focus on the problem in general.

Algorithmic Thinking

An algorithm is simply a recipe, or set of instructions, for solving a problem. It takes certain inputs (known as arguments) and calculates an output (the return value).

Now it is time to write code. To have a logical and to produce the outcome that you desire, you have to write your code in good order and step by step until you achieved the main result.

Debugging And Testing

The concept of debugging is very important in computational thinking. This is because we may not get the right output or solution of a program even if it is correct. When there are errors in the process of writing a program, this is called debugging. It can be either syntax error or logical error. Since students tend to write programs only by mimicking the output of others, they do not understand how to solve a problem when their code does not work for them.

Check every part of your code and try to play with it to know where the problem is in order to have a new solution.


Problem-solving is the most important skill that a programmer must have. without it, the programmer will just copy and paste other codes without inventing anything new.

Problems are everywhere and with computational thinking, you will be able to solve them and come up with a good solution.

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