Snake has one of the most storied histories in gaming, tracing its origins back to the 1976 arcade game Blockade by Gremlin Industries. The concept was refined through various iterations on early personal computers during the 1980s, but it achieved global cultural icon status when Nokia pre-installed a version called Snake on the Nokia 6110 in 1997. By the time the Nokia 3310 launched in 2000, Snake (specifically Snake II) had become the most widely played mobile game in the world, introducing hundreds of millions of people to mobile gaming years before smartphones existed. The game's enduring popularity stems from its perfect simplicity: move, eat, grow, survive.

From a technical perspective, Snake is an excellent case study in game loop architecture. The game loop is the heartbeat of any real-time game, typically consisting of three phases: process input, update game state, and render. In Snake, the game loop runs at a fixed tick rate (the speed setting), and during each tick the snake advances one cell in its current direction. The game state update involves moving the head to a new position, checking for collisions, and either growing the tail (if food was eaten) or removing the last tail segment. This fixed-timestep approach, as opposed to variable-timestep rendering, ensures consistent gameplay regardless of device performance.

Collision detection in Snake uses a straightforward but instructive algorithm. The snake's body is typically represented as an ordered list of coordinate pairs (a queue or deque data structure). Wall collision is detected by checking whether the head's new position exceeds the grid boundaries. Self-collision requires checking whether the head's new coordinates match any existing body segment, which in a naive implementation is O(n) where n is the snake's length. Optimized implementations use a hash set of occupied coordinates for O(1) lookup, a practical lesson in how data structure choice impacts performance.

The food placement algorithm must also avoid spawning food on any cell currently occupied by the snake. As the snake grows longer and occupies more of the grid, the number of valid placement cells decreases, and the naive approach of randomly guessing until finding an empty cell becomes inefficient. A more sophisticated approach maintains a set of unoccupied cells and samples directly from it. This natural difficulty curve, where the game becomes harder as you succeed because the snake occupies more space and there is less room to maneuver, is an elegant emergent property of the game's simple rules rather than an explicitly programmed difficulty system.