Factorial Memes

The villain's journey from smug confidence to existential dread is the perfect metaphor for recursive functions gone wrong. First panel: "Look at my elegant factorial function!" Second panel: "Let me call it with 5, what could go wrong?" Third panel: "Watch as it multiplies its way down..." Fourth panel: "OH GOD THE STACK IS COLLAPSING." The classic rookie mistake - forgetting your base case in recursion. The computer keeps calling the function deeper and deeper until it runs out of memory. It's like telling someone to look up a word in the dictionary, but the definition just says "see definition of this word."

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.