Hey Africoders! As a computing student, I recently went through the interview process for the Google Developers Student Club (GDSC) at my university. While prepping, I spent a whole night diving into the world of data structures. Even though data structures are officially on the curriculum next semester, I knew understanding them would be beneficial. (Spoiler alert: it was!)
While data structures didn’t come up directly in my interview, the knowledge I gained has already proven valuable. Now, I’m eagerly awaiting feedback to see if I’ll get the chance to lead the GDSC chapter on our campus. Fingers crossed!
In the meantime, I wanted to share what I learned about data structures in that intense night of studying. Let’s jump in!
What are Data Structures?
Imagine a cluttered desk overflowing with papers. Finding anything specific would be a nightmare, right? Data structures are like organized filing cabinets for your computer’s memory. They define how data is stored and accessed, making it efficient to find, add, or remove information.
Types of Data Structures and Their Real-World Applications:
Arrays: Think of these as rows and columns in a spreadsheet. Arrays store items of the same data type in a contiguous memory block, making them super-fast for accessing elements by their position. They’re used everywhere, from storing student grades in an application to representing pixels on your computer screen.
Stacks: Imagine a stack of plates. You can only add or remove plates from the top. Stacks follow a “Last In, First Out” (LIFO) principle. They’re used in things like the browser’s back/forward history and for undoing/redoing actions in software.
Queues: Unlike stacks, queues function like a line at a coffee shop. The first person in line gets served first (FIFO - First In, First Out). Queues are perfect for managing print jobs or tasks waiting to be completed by a computer program.
Linked Lists: These are flexible data structures where elements (nodes) are connected by links instead of being stored in a continuous memory block. Linked lists are great for representing social media feeds where new posts are constantly added at the top.
Trees: Imagine an organizational chart of a company. Trees are hierarchical structures where elements (nodes) have a parent-child relationship. They’re used for efficient searching and sorting of data. For example, binary search trees are used in autocomplete features and file systems on your computer.
Graphs: Imagine a social network where users are connected to each other. Graphs represent relationships between entities, like cities connected by roads or web pages linked by hyperlinks. They’re used in recommendation systems, navigation apps, and analyzing social connections.
This is just a glimpse into the fascinating world of data structures. Each type has its strengths and weaknesses, making them suitable for different tasks.
Let me know in the comments below!
- What other data structures have you come across?
- How do you think data structures are used in everyday applications you use?
I’m excited to continue learning and share more tech adventures with you all!
