In this blog post, I’ll explore the similarities between cooking kimchi stew and algorithms from the perspective of clear and efficient problem-solving.

How to Cook Kimchi Stew? It’s an Algorithm!

How do you cook kimchi stew?
1. Put water in a pot and bring it to a boil.
2. Add a suitable amount of properly prepared kimchi and let it simmer.
3. Once cooked, adjust the seasoning and finish it off.
If explained this way, most people would be baffled and raise an eyebrow. But strictly speaking, we cannot say that the above explanation is not a method for making kimchi stew. It’s just that while it’s very vague, it’s not entirely wrong. This explanation actually captures a part of the problem-solving process. We call the method of systematically explaining this problem-solving process an “algorithm.”

What is an algorithm?

An algorithm refers to a step-by-step procedure or method for solving a problem. The example of cooking kimchi stew mentioned above is also a type of algorithm. However, it cannot be called a “well-designed algorithm.” A well-designed algorithm refers to a procedure that includes a clear, efficient, and logical explanation applicable to all situations.

Clarity of Algorithms

When an algorithm is clear, it means there is no confusion or ambiguity for the reader to understand it. For example, the expression “a suitable amount” mentioned above is very ambiguous. Since people may interpret “a suitable amount” differently, this is not a clear explanation. To create a clear algorithm, it must be made more specific.
Let’s express the method for making kimchi stew a little more clearly.
1. Add 500–550 ml of water (at 4°C) to a pot and bring to a boil.
2. Cut the kimchi into squares or rectangles with sides approximately 3 cm long, then add 40 g of kimchi per 100 g of water and boil.
3. Once the kimchi is cooked, adjust the seasoning and finish the dish.
In this way, using specific numerical values instead of vague terms like “appropriate amount” can enhance the clarity of the algorithm. Here, “clarity” is essential. To ensure that the process of making kimchi stew isn’t interpreted differently by each person, clear standards and steps must be provided to achieve consistent results.

Algorithm Efficiency

An algorithm must not only be clear but also efficient. In other words, it is important to minimize the time and resources required to solve a problem. In computer science, in particular, when the size of the input is very large, processing time can vary significantly depending on the algorithm’s efficiency.
For example, the details of the algorithm may not make a big difference when making a single bowl of kimchi stew, but the story changes when you need to make hundreds of bowls. This is because the completion time of the dish varies greatly depending on what constitutes “proper preparation” and how long that preparation takes.

Algorithms and Daily Life

In computer science, algorithms are used to solve various problems in our daily lives. A prime example is the algorithm that finds the shortest route in a car navigation system. It must quickly determine the shortest route by considering various variables such as real-time traffic conditions, accidents, and average speeds. Solving such problems requires a highly efficient and clear algorithm.
Algorithms are applied in various places in daily life that we might not even realize. For example, internet search engines use algorithms to quickly and accurately find the desired information from a vast amount of data. Algorithms also play a crucial role in sorting large-scale data or filtering it according to specific criteria. The purpose of an algorithm is to solve problems quickly and accurately.

Real-World Applications of Algorithms

In reality, algorithms are not merely academic concepts. We utilize algorithms in many cooking recipes and in the process of solving everyday problems. Just as cooking kimchi stew requires following the proper ingredient ratios, cooking times, and sequence to achieve the ideal flavor, algorithms exist to provide optimal solutions in various problem situations.
Not only in computer science but also in many aspects of daily life, we often follow algorithms unconsciously. We solve problems through established procedures and steps, and in the process, we continuously improve the algorithms based on our experiences.