Data structures and algorithms provide a set of approaches for efficiently handling data. So programmers need to have a strong understanding of DSA fundamentals to write efficient and correct code. There are two main reasons for this:
Before I went to college, I had no experience with computers. In my first year, I failed the programming course. I tried asking seniors for advice, but I didn't receive a clear answer. I was ready to give up on computer science altogether.
But then, in my third year, one of my friends explained a recursive algorithm for finding the nth Fibonacci number to me and pointed out that it had an exponential time complexity of n. This meant that a computer would take years to produce the output for a large value of n. I was surprised and asked why most students wrote this code during their first-year exams. He told me that they just memorized it and didn't think about its performance. Then, he showed me a linear-time solution using a bottom-up approach of dynamic programming, which he even further optimized to a single-loop solution with constant extra space.
This was the first time I truly understood the importance of algorithms and how they could make a huge difference. As Steve Jobs said, "We can't connect dots looking forward; we can only connect them looking backwards." From then on, I became fascinated with coding problems and comparing the efficiency of different solutions. I even read the book "CLRS" twice out of curiosity!
This experience helped me change my mind about my career path and realize that programming is not just about syntax and writing correct code, but also about designing efficient algorithms!
While it is important to have a good understanding of programming languages, the real satisfaction comes from having a strong command of problem-solving strategies in DSA. Consistent practice and exploring real-world applications can help change our perspective on the importance of algorithms.
After six years of teaching experience with students and professionals, I have identified four good reasons to learn data structures and algorithms:
The system performance depends on choosing efficient algorithms as much as on choosing fast hardware. Even applications that do not require algorithms directly at the application level…relies heavily upon algorithms. For examples:
Overall, algorithms are at the core of most real-life applications. Just as rapid innovations are being made in other computer technologies, they are also being made in algorithms.
In an age where we can use library functions to write software code, it may seem unnecessary to learn algorithms and data structures. However, it is important to understand the implementation details, even when they are hidden behind an abstraction. In other words, mastering DSA helps us to better understand how to effectively use library functions and other abstractions in our code.
Tech companies often test candidates' knowledge of data structures and algorithms (DSA) during the interview process because they need to hire programmers who can efficiently solve complex, large-scale, data-intensive problems. A strong understanding of DSA is a clear indicator of a programmer's ability to come up with smart solutions to these types of problems in terms of time and memory. In other words, a programmer who is proficient in DSA is better equipped to handle the data-intensive challenges faced by tech companies.
Algorithmic logic is often found in beautiful natural patterns and real-life activities. It can be concise and straightforward, effectively performing a single task. As Donald Knuth said, "People who analyze algorithms have double happiness. First of all, they experience the sheer beauty of elegant mathematical patterns that surround elegant computational procedures. Then they receive a practical payoff when their theories make it possible to get other jobs done more quickly and economically."
This highlights the dual benefits of studying algorithms: the aesthetic pleasure of discovering elegant patterns, and the practical value of being able to solve problems more efficiently. Enjoy learning, Enjoy coding, Enjoy algorithms :)