Uncovering Algorithms and Data Structures: The Foundation of Efficient Programming

In this series of posts, I will share my learning journey about two topics that are widely discussed in both academic environments and large technology companies: algorithms and data structures. Although these topics may seem daunting at first glance, especially for those like me who haven't had the opportunity to delve into them throughout their career due to other professional challenges, my goal is to make them accessible.

I'll start with the most basic concepts and move on to more advanced topics, creating a record of my evolution. I hope these posts are also useful for anyone on the same learning path. To delve deeper, I will use a combination of practical challenges on platforms like LeetCode, as well as readings and discussions about the theory behind each algorithm. The programming language I chose for this journey is JavaScript.

Why is studying algorithms worth it?

Algorithms and data structures are fundamental components in building any software. Many of them are the result of years of study aimed at efficiently solving complex problems, and can be applied in different areas of IT, such as web development, backend, artificial intelligence, among others. Understanding algorithms is a great way to write optimized code. Furthermore, mastery of these concepts is often assessed in technical interviews at large technology companies, which can be interesting for those who want to join one of these giants.

What are algorithms?

Algorithms are sets of instructions that solve a problem. A common analogy I heard in college is that of a cake recipe: you follow a series of steps to obtain the final result, that is, the cake.
According to the book Introduction to Algorithms, it explains that an algorithm takes a value or a set of values ​​as input and generates a value or set of values ​​as output. A more practical example, aimed at development, would be: imagine that you have a disorganized list of numbers and you need to order them from smallest to largest. In this case, the unordered list is the input, and the algorithm is the sequence of steps that rearranges the numbers, generating the ordered list as output.

What are data structures?
Data structures are ways of organizing and storing information so that we can access and use it when convenient. If we think about a bookshelf, we can see that books can be organized in several ways: by theme, author, alphabetical order, color, among others. The way we choose to organize them directly influences the ease with which we find a specific book.

As we progress through this series, my intention is to demystify these topics and build a solid foundation of knowledge, both for myself and for anyone following my posts. The journey to mastering algorithms and data structures can be challenging, but with regular practice and curiosity, I believe we can all overcome the initial difficulties and reach a level of proficiency that meets market requirements, as well as becoming more efficient and efficient developers. able to solve problems optimally.

I hope this exchange of experiences is as enriching for my learning as it is for yours. And that, in addition to being productive, this process can even be fun. Feel free to suggest topics, new tools, study materials or even additional challenges. I'll love learning together with you!

References

Cormen, T. H., Leiserson, C. E., Rivest, R. L., & Stein, C. (2009). Introduction to Algorithms (3rd ed.). MIT Press.

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