How can you apply algorithm development in your career?

In my view, algorithm development is essential for career growth because it involves creating efficient methods to solve problems. Mastering this skill allows you to design solutions that enhance processes and improve decision-making across different fields. By applying these techniques, you position yourself as someone capable of tackling complex challenges and driving innovation.

Algorithm development is at the heart of computer science and software development. A computer has limited CPU and memory which means you have to use highly optimized algorithms in order to ensure that we make the best usage of available resources. Thankfully computer scientists have already developed a lot of quality algorithms. We just have to use them correctly to ensure that our software is blazingly fast.

Any problem-solving method can be considered an algorithm. Algorithms are as crucial to my work as mathematics is to other natural sciences. When I was in school, many of my friends didn't value math. They often told me that I spent a lot of effort solving integrals, but later I wouldn't be able to calculate as quickly as vegetable sellers, and things like integrals could be solved by computers anyway. In reality, besides the broad applications of math, especially in computer science, after hours of thinking hard about math problems, you develop strong logical thinking and perseverance. I hope that my examples about math help you better understand the importance of algorithms and their development.

I always approach complex or ambiguous tasks using the divide and conquer method. You know, it’s difficult to evaluate or estimate the processing time of a complex task. So, I break it down until each subtask is manageable for me. Another example is when the system has an issue, it's challenging to pinpoint where the problem lies. Using various methods, we need to narrow down the scope to identify the root cause.

There are many algorithms that demonstrate we can improve speed by using more memory. Over time, the cost per unit of memory decreases, while faster processing becomes increasingly valuable. This greatly assists me in software design and development. For instance, using cache to retrieve data faster; eliminating recursion with a stack; representing RBAC information in binary, converting it to base 10, and storing it, making permission checks easy and fast with bitwise operators; etc.