The Dictator's Guide To Efficient Sorting

The face every senior dev makes when some kid who just discovered "Hello World" starts dropping hot takes about the industry. That classic list of naïve programming opinions is what we veterans call "peak Dunning-Kruger." Sure, LeetCode will definitely prepare you for building enterprise systems that handle millions of users. And yes, we senior engineers just type "how to code good" into Google faster than juniors. Nothing says "I've never built anything real" quite like claiming backend is just "hitting APIs." Eight years of experience? More like eight minutes on a JavaScript tutorial.

Sure, normal people count to 10 on their fingers. But us nerds? We're out here counting in binary where each finger is a bit. Two hands = 10 bits = 2^10 = 1024 values. It's the same reason we think 512MB is a nice round number while marketing folks insist on calling it "half a gig." We didn't spend years optimizing algorithms just to use decimal like some kind of animal. The irony? Most of us still use our fingers to count how many bugs we've introduced while fixing the original one.

This is a brilliant play on Big O notation, the bane of every algorithm class! The computer nerd's algorithm is O(1) - constant time complexity, the holy grail of efficiency. The A-student's algorithm is O(N) - linear time that scales with input size, respectable but not perfect. And then there's "my algorithm" at O(N!) - factorial time complexity, which is basically computational suicide. It's the difference between your code finishing in microseconds versus the heat death of the universe. The exclamation point is both the factorial notation AND the appropriate reaction when you realize your algorithm will take longer to run than the lifespan of several stars.

Journalists discovering that 256 is an "oddly specific number" while every developer is facepalming so hard they've left a permanent mark. For the uninitiated: 2^8 = 256, which is a power of 2 that makes perfect sense when you're allocating memory or designing data structures. It's like watching someone be confused why pizza comes in 8 slices instead of a "nice round 10." Next headline: "Developer uses 65,536 as maximum file size - sources say he 'just made it up'."

The professor asked for a pattern program, and this student just hard-coded every single line with printf statements. No loops, no logic, just brute force printing. And now they're running away from the teacher because they know what's coming. It's the coding equivalent of answering "what's 5+7?" by saying "I memorized that it's 12" instead of explaining addition. Sure, it works... technically. But you've missed the entire point of the exercise and any self-respecting CS professor is going to hunt you down for this crime against algorithms.

The eternal holy war of programming: zero-indexing vs one-indexing. Some languages start arrays at 0 (looking at you, C and friends), others insist on starting at 1 (MATLAB and Lua, you rebels). Then there's that one galaxy-brain developer who suggests starting at 0.5 as a "compromise." Because nothing says "I've solved computer science" like introducing floating point errors into your array indices. Next brilliant idea: using π as the starting index – because irrational numbers make PERFECT sense for memory addressing!