#Algorithms
11 notas · última:
What computer science concepts should devs without a CS background prioritize learning?
The thread points to data structures, algorithms, Big O, and lambda calculus as the core CS ideas for self-taught devs, with comments adding databases, clean code, concurrency, and basic engineering skills.
Learn Big O Notation once and for all
The post reviews Big O notation as a way to describe how runtime grows with input size and walks through common classes like O(1), O(n), O(n^2), O(log n), O(n log n), O(2^n) and O(n!).
O(n) Solution to the Multiply Others Problem in F#
Yan Cui walks through a division-free, O(n) F# solution to the classic interview question of multiplying every array element except itself.
Functionally Solving Problems
A Learn You Some Erlang chapter that solves an RPN calculator and a shortest-path puzzle with folds and pattern matching instead of hand-rolled recursion.
14 Patterns to Ace Any Coding Interview Question
The article groups coding interview questions into 14 recurring patterns, showing how to identify each one and which kinds of problems it fits, so practice can focus on templates instead of isolated drills.
What I Learned About C# From Job Interviews
The post explains which C# features help in coding interviews, from multidimensional arrays and tuples to bitwise operators, string and array helpers, plus practical interview habits.
Stop Fearing the Whiteboard. Conquer It.
The article argues that whiteboard interviews are part of hiring and can be handled with basic study, pen-and-paper practice, and repeated coding challenges. It lays out a three-step prep plan.
The Worst Programming Interview Question I've Ever Seen ! - A CODER'S JOURNEY
The post argues that asking candidates for a closed-form formula for 1 to 1000 tests memorization more than problem solving, can misjudge fit, and is poorly aligned with most software jobs.
Tips for tasks on Codility
The post lists practical ways to prepare for Codility tests, from practicing the demo and reviewing algorithms to handling edge cases, unit tests, and the test environment.
7 timeless lessons of programming graybeards
The article argues that older programmers still have practical advantages because experience teaches limits that hype hides: memory, network latency, compiler bugs, user speed, algorithmic complexity, and library costs.
Great Algorithms that Revolutionized Computing
The page lists algorithms that changed computing, grouping them by compression, cryptography, search, sorting, mathematics, and graphics, and noting what each one is used for.