Improving your Algorithms & Data Structure Skills
Last updated
Last updated
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Some of the resources in this article originally appeared in one of my comments on a reddit post that became quite popular. Here’s the thread, and my new write-up is below.
Data Structures
Learn about arrays, linked lists, binary trees, hash tables, graphs, stacks, queues, heaps, and other fundamental data structures.
Math & Logic
You’ll need to know some mathematical concepts from several different areas if you want to excel at algorithms. Learn about set theory, finite-state machines, regular expressions, matrix multiplication, bitwise operations, solving linear equations, important combinatorics concepts such as permutations, combinations, pigeonhole principle.
Computer Architecture
Learn how data is represented in a computer, the basics of digital logic design, boolean algebra, computer arithmetic, floating-point representation, cache design. Try and learn a little about C and Assembly programming.
Once you feel like you have a good understanding of most of the concepts listed above, it’s time to start diving into the algorithms part. Here is a list of resources and things I did to get better at writing and understanding important algorithms.
Big-O & Runtime
Implement Some Algorithms Yourself
Start off by implementing several important algorithms yourself and learning about their running times. Some examples are:
Binary search
Euclid’s algorithm
Depth and breadth first search
Dijkstra’s shortest path
Binary tree traversals
Insertion sort, Mergesort, Quicksort
Min & max heaps
Algorithm Books
Challenges
Algorithms Explanations & Interview Questions
Dynamic Programming
A method for solving a complex problem by breaking it down into a collection of simpler subproblems, solving each of those subproblems just once, and storing their solutions. The next time the same subproblem occurs, instead of recomputing its solution, one simply looks up the previously computed solution, thereby saving computation time.
Advanced Resources in Algorithms (optional)
The first thing you’ll need if you want to get better at algorithms and data structures is a solid base. This base can be learned one of several ways, either through a computer science program at university, some focus a bit on the topics below, or you can learn on your own from , videos, or lectures. So you’ll need a basic understanding of the following topics to get started:
Pages taken from .
Learn what is and how to analyze the of algorithms. This is a on the topic (here is the chapter on the ).
Here is a good that teach algorithms.
and .
Read the . It’s a great book and it’s my favorite.
is a classic book that covers a lot of material.
contains a lot of challenges and code solutions that will help you prepare for interviews.
Practice coding simple and then more advanced algorithms on sites like and which provide explanations and solutions so you can learn from other coders as well.
Go through the challenges on this .
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Read as many algorithm explanations and code examples as you can on . Here is an of a good post on graph algorithms.
Look at some interview questions posted on and try and understand how other users solved the questions. Like .
Aside from coding challenge sites, try and solve common coding interview questions you find online .
This a very you will need to understand if you want to get better at algorithms, which is the reason I separated this topic from the rest. The description from Wikipedia for it is (bolding is mine):
I have seen dynamic programming show up in several coding interviews I’ve had. I’ve also seen problems that require a dynamic programming solution on challenge sites like , , and several challenges on required a DP solution.
I’d recommend to try and solve as many as you can. There is also a good tutorial on TopCoder titled: . A lot of DP problems have the same structure and patterns so if you solve 3 DP problems everyday for 2 weeks or so, after a while you’ll be able to spot and solve a DP problem no problem.
Lectures by
by Erik Demaine
: A wiki dedicated to competitive programming
problems and algorithms ( and , but can get quite difficult)
: implementation and analysis of data structures for sequences, queues, priority queues, unordered dictionaries, ordered dictionaries, and graphs
I hope you enjoyed this list of resources. Feel free to practice coding on , and comment below with any other resources you think are helpful.
