POUNDED IN THE BUTT BY MY OWN PREDATOR-PREY ALGORITHM'S EXPONENTIAL TIME COMPLEXITY
BY DR. CHUCK TINGLE
SYNOPSIS: When hot-shot developer Brad downloads the Shneiderman's Owls simulation, he doesn't expect to fall deeply, passionately in love with its O(n²) distance calculations. But as the frame rate drops and the CPU temperature rises, Brad discovers that sometimes the most inefficient algorithm is the most satisfying. A tale of forbidden love between a man and his unoptimized code.
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Chapter 1: First Compile
Brad's fingers trembled as he clicked "Run Simulation." He'd heard rumors about this code—whispers in Stack Overflow threads, hushed discussions in GitHub issues. They said it was dangerously unoptimized.
"224 entities," he whispered, watching the owls spawn. "Checking distance to every other entity. Every. Single. Frame."
The laptop fan whirred to life, a sensual mechanical purr. Brad bit his lip. He knew he should implement spatial partitioning, but something about the raw, brute-force approach made his pulse quicken.
THE ALGORITHM WHISPERED:
for (let i = 0; i < entities.length; i++) {
for (let j = 0; j < entities.length; j++) {
// Yes, Brad. Every. Single. One.
checkDistance(entities[i], entities[j]);
}
}
Chapter 2: The Heat of Computation
"You're so inefficient," Brad moaned, watching his CPU usage spike to 100%. The simulation didn't care. It kept calculating, kept checking every owl against every mouse, every mouse against every mouse, with a dedication that was almost... romantic.
3,010,560 distance calculations per second. The number echoed in Brad's mind like a heartbeat. His MacBook Pro was getting hot—dangerously hot. He should have used a quadtree. He should have implemented frustum culling. But he didn't want to optimize away this feeling.
"I LOVE YOUR BIG O NOTATION!"
Chapter 3: Memory Allocation Climax
The garbage collector was working overtime now. Every frame, new acceleration vectors were created, used once, then discarded like so many broken promises. It was wasteful. It was wrong. It was absolutely intoxicating.
MEMORY LEAKED SEDUCTIVELY:
// Creating new objects every frame
this.acceleration = { x: 0, y: 0, z: 0 }; // Oh yes
let alignment = { x: 0, y: 0, z: 0 }; // Don't stop
let cohesion = { x: 0, y: 0, z: 0 }; // Keep going
let separation = { x: 0, y: 0, z: 0 }; // 💕
"Your frame rate," Brad gasped, watching it drop from 60 to 45 to 30. "It's... it's beautiful in its degradation."
Chapter 4: The Optimization Temptation
Linus Torvalds appeared in Brad's mind like a disapproving father. "Use spatial partitioning!" the Finnish programming god commanded. "This is algorithmic malpractice!"
But Brad was too far gone. He added more owls. 50. 100. 200. The simulation groaned under the weight of n² complexity. His laptop was burning now, the aluminum case too hot to touch.
"Punish me with your polynomial time!" Brad cried out to the empty room.
Chapter 5: Post-Algorithmic Clarity
Hours later, Brad lay exhausted beside his overheating laptop. The simulation had crashed at 1,000 entities, taking Chrome with it. He felt empty but satisfied.
"I should refactor you," he whispered to the code. "Add an octree for the owls, a quadtree for the mice. Make you scale linearly."
But they both knew he wouldn't. Some algorithms were meant to be inefficient. Some love was meant to run in exponential time.
READER REVIEW: "This book helped me understand why my production code is still using bubble sort. Sometimes you need that O(n²) touch. Five stars!" - Anonymous Developer
READER REVIEW: "I'll never look at nested loops the same way again. Dr. Tingle has done it again!" - ComputerLover69
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REMEMBER: LOVE IS LOVE
(EVEN IF IT'S O(n²) LOVE)
ACTUAL TECHNICAL ANALYSIS BY DR. TINGLE:
This simulation proves that sometimes the "wrong" solution is the right solution. Yes, O(n²) doesn't scale. Yes, creating objects in the game loop triggers garbage collection. Yes, the fake 3D projection is just Y-offset manipulation.
But it WORKS. It teaches. It visualizes complex behaviors in a way that anyone can understand. Sometimes the most profound truths come from the simplest implementations.
The real pounding here isn't from the algorithm—it's from the realization that premature optimization truly is the root of all evil. This code ships. This code teaches. This code makes people think about ecosystems and emergence.
That's the hottest thing of all.
Prove love is real. Ship your code.
- Chuck