Quant Memo
Core

Induction and Recursive Structure in Puzzles

If a puzzle at size n reduces to the same puzzle at a smaller size plus a small fixed piece of work, solve the small case, find the step, and the general answer falls out.

Prerequisites: How to Attack a Brainteaser

A puzzle stated for "n coins" or "n people" or "a chessboard of any size" is rarely meant to be solved from scratch at every size. If solving the size-nn version can be reduced to solving the size-(n1)(n-1) version plus one small, fixed piece of extra work, you only need two things: the smallest case, solved directly, and the reduction step, applied over and over. That pair is a complete proof for every nn.

Worked example: tiling a deficient board with L-trominoes

A 2n×2n2^n \times 2^n board has one square removed, anywhere on the board. Prove it can always be tiled exactly by L-shaped trominoes (three squares in an L), each covering three cells.

Base case, n=1n=1. A 2×22\times2 board with one square removed has exactly three squares left, and those three squares always form an L-shape. One tromino tiles it. Done.

The reduction. Assume the claim is true for every 2n1×2n12^{n-1}\times2^{n-1} board with one square missing. Take a 2n×2n2^n\times2^n board with one square missing, and cut it into four quadrants, each 2n1×2n12^{n-1}\times2^{n-1}. One quadrant already contains the missing square. Place a single tromino at the very centre of the whole board, covering exactly one cell from each of the other three quadrants. Now all four quadrants have exactly one square "missing" — the original hole in one, and one tromino cell each in the other three. By the assumption, each quadrant can be tiled on its own. Combine the four tilings and the one centre tromino, and the whole board is tiled.

hole already here centre tromino: one cell per remaining quadrant four smaller boards, each now with exactly one missing cell
The centre tromino turns one big deficient board into four smaller deficient boards, each solvable by the same argument one size down.

An inductive puzzle solution needs exactly two pieces: the smallest case, checked by hand, and a reduction that turns the size-nn problem into one or more copies of the size-(n1)(n-1) problem plus a fixed amount of extra work. Once both are nailed down, every size is covered.

The same shape solves the Tower of Hanoi (moving nn disks reduces to moving n1n-1 disks twice, plus one move of the largest disk), and "prove a straight line always splits the plane into at most (n2)+n+1\binom{n}{2}+n+1 regions with nn lines" (adding the nn-th line to an (n1)(n-1)-line arrangement crosses at most n1n-1 existing lines, adding at most nn new regions).

When a puzzle is parameterised by nn, ask two questions in order: what does the n=1n=1 or n=2n=2 case look like, and can I build the nn-case out of one or more (n1)(n-1)-cases plus something small and fixed? If yes to both, you're done — resist the urge to solve n=5n=5 by hand to "check."

Sizing algorithms lean on the identical habit: a recursive backtest or a divide-and-conquer routine is trusted once its base case and its recursive step are each verified, not because every intermediate size was tested by hand.

Related concepts

Practice in interviews

Further reading

  • Engel, Problem-Solving Strategies (ch. 5)
ShareTwitterLinkedIn