#Data-Structures
6 notas · última:
Optimizing Javascript for fun and for profit
The page collects practical JavaScript optimization habits: avoid unnecessary work, string comparisons, shape changes, indirection, cache misses, large objects, and weak data structures, while insisting that benchmarking and profiling come first.
Good programmers worry about data structures and their relationships
The piece argues that good software starts with the data model, because clear data structures make code easier to design, maintain, and extend, and can replace complexity in logic.
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.
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.
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.
Simple and Clean Code vs. Performance
The article argues that simple, clean code should be the default. It separates efficiency from performance, says most code is not a bottleneck, and recommends profiling before sacrificing readability.