I'm starting a university course on data structures and algorithms next semester, and I'm feeling overwhelmed about where to begin. The material will cover arrays, linked lists, trees and graphs, stacks and queues, symbol tables, priority queues, balanced trees, sorting algorithms, and complexity analysis. The course will probably use C++, since the prerequisite did too, and it sounds like it may be fairly theory-heavy. My professors don't usually provide many resources or release slides early, so I'd like to study ahead of time. Should I buy a textbook, follow a particular learning path, or practice problems online? I'm worried about falling behind and hurting my grades, so I'd appreciate advice on how to approach the subject without panicking.
4 Answers
You don’t need to prepare the entire course before the semester begins. Start with one structure, write a few small programs using it, and test its operations yourself. Read the assigned textbook if there is one, or choose a well-regarded introductory book if there isn’t. Consistent study each week will help much more than trying to learn everything in one intense burst.
Focus less on memorizing a collection of structures and more on learning when each one is appropriate. For example, use a set when values must be unique, a map when you need key-to-value lookup, a priority queue when you repeatedly need the highest- or lowest-priority item, and a graph when relationships between objects matter. Also pay close attention to complexity analysis—being able to explain why one solution is O(n) and another is O(n²) is often more important than memorizing code.
Practice problems are useful, but don’t just grind random exercises immediately. Pick a problem, attempt it with what you already know, and then study the technique or data structure that solves it more efficiently when you get stuck. That process helps you understand why a hash table, heap, tree, or graph is useful instead of memorizing definitions. Balanced trees may take extra time, so don’t worry if they don’t click right away.
It’s also normal for the subject not to click on the first attempt. Working on small programming projects or classic algorithm problems can make the theory much easier to understand because you start seeing why an inefficient solution needs to be improved.
The simplest way to get ahead is to choose a solid textbook and work through it from the beginning. Don’t try to learn every topic at once: start with arrays, linked lists, stacks, and queues, then move into trees, hash tables, heaps, graphs, sorting, and complexity analysis. Implement each structure in C++ yourself instead of only reading about it, and make sure you understand the time and space cost of common operations.
A good exercise is to implement an algorithm in a basic form first, such as a sorting function taking a pointer and length, and then compare it with modern C++ approaches using containers or spans. That gives you both the underlying theory and familiarity with practical C++.