Hello, I am Rutik, today I am giving you information on why data structures and algorithms are so important to learn. If you like this information, please share it with your friends. Comment to improve my writing skills and subscribe by email for future updates.
Many young programmers scour the web trying to find answers to this question: How to study Algorithms and Data structure? Certainly, a good place to start… But I believe a more relevant question would be this: What are algorithms and data structures, and why should I study them?
Let’s start
What is an Algorithm?
Wikipedia says “an algorithm is a self-contained step-by-step set of operations to be performed. Algorithms perform the calculation, data processing, or automated reasoning tasks.”
You’d be surprised that there are still some of us who could be tripping on words while trying to explain algorithms, data structures, and their importance. Simply put, whether you are cooking a burger or adding two numbers, there’s an algorithm working its magic there. From monitoring stock markets to oil crises to determining crop yield to pairing soul mates, algorithms are omnipresent.
One definition from the Internet is this: An algorithm is a detailed step-by-step instruction set or formula for solving a problem or completing a task. You need to tell your computer what task to perform, right? You need algorithms or specific computational procedures to achieve the input-output relationship. Repetition, sequencing, and conditional logic or decision are computational concepts that manifest in your everyday life. Your morning routine can be an algorithm.
Algorithms are much more than instructions. It doesn’t matter if you call them algorithms or programming basics, what matters is that they teach you to define clear steps and conceptualize solutions in terms of distinct steps in a process.
What is Data Structure and why study it?
No biggie this data structure refers to an orderly arrangement of data. Something you need when you are arranging key documents in folders in a filing cabinet. Imagine a legal clerk’s life without such a system! Shudder. Be it an encyclopedia or a bank statement, there is nothing random about these data summaries. Think not binary trees or associative arrays; think a shopping list. Is Mucho easier? Data structures store objects and allow their manipulation. You call a mathematical model of a data structure an abstract data type (ADT). Here, binary relationships can link objects. Data structures can be linear (arrays, stacks, linked lists, or queues) or nonlinear (trees, graphs, tables, or sets).
Why am I talking about them? Well, abstractions help scientists focus on what’s really important, the big picture, and not exhaust their energies on the nitty-gritty. ADT is a specification mechanism and is important for organizing and manipulating data. A graph of fluctuating stock prices is an abstraction of how the money markets in the world are doing. Or another everyday example of abstraction will be the car getting me to Walgreens to get Tylenol without me knowing exactly what’s happening under the hood.
Objects plus Operations equal ADT. The implementation is hidden. That is, the client knows what the operations are but don’t know how the type is implemented. For example, to define an ADT, you will, therefore, need to define fields in a record or class and the routines or methods. Say, your library changes the program to store when overdue fines need to be paid. Although you might not know it, you are going to be shelling it out if need be. But a data structure tells you how ADT is implemented and unlike the latter, it also tells you how the data is stored and how the operations work. For instance, Java source code should be accessible only to those who implement the classes, so other programmers can’t tamper with the software.