Recursion and Dynamic Programming
Fibonacci with Memoization
Compute fib(n) recursively. Cache each fib(k) in a memo map so each
subproblem is solved at most once.
Algorithm
Canonical input n = 6 produces fib(6) = 8. Replay highlights every
memo write and every cache hit.
memoization
A `Map<number, number>` cache stores each completed subproblem. Before recursing, check the memo: a hit returns immediately, a miss descends.
explicit memo parameter
Pass the memo as an explicit parameter so the lesson stays about caching, not language-level scoping.
Basic Implementation
basic.ts
Replay: real traced execution (multi-file project)
function fib(n: number, memo: Map<number, number>): number {
if (memo.has(n)) {
return memo.get(n) as number;
}
if (n < 2) {
memo.set(n, n);
return n;
}
const value: number = fib(n - 1, memo) + fib(n - 2, memo);
memo.set(n, value);
return value;
}
const memo: Map<number, number> = new Map();
const result: number = fib(6, memo);
console.log(result);
console.log(JSON.stringify(Object.fromEntries(memo)));
memo ← {}, action ← miss -> descend fib(5)
8}9const value: number = fib(n - 1, memo) + fib(n - 2, memo);10memo.set(n, value);values this step{}memomiss -> descend fib(5)action6nmemo ← {}, action ← miss -> descend fib(4)
8}9const value: number = fib(n - 1, memo) + fib(n - 2, memo);10memo.set(n, value);values this step{}memomiss -> descend fib(4)action5nmemo ← {}, action ← miss -> descend fib(3)
8}9const value: number = fib(n - 1, memo) + fib(n - 2, memo);10memo.set(n, value);values this step{}memomiss -> descend fib(3)action4nmemo ← {}, action ← miss -> descend fib(2)
8}9const value: number = fib(n - 1, memo) + fib(n - 2, memo);10memo.set(n, value);values this step{}memomiss -> descend fib(2)action3nmemo ← {}, action ← miss -> descend fib(1)
8}9const value: number = fib(n - 1, memo) + fib(n - 2, memo);10memo.set(n, value);values this step{}memomiss -> descend fib(1)action2nmemo ← {1: 1}, action ← base 1; memo.set(1, 1); return
8}9const value: number = fib(n - 1, memo) + fib(n - 2, memo);10memo.set(n, value);values this step{1: 1}memobase 1; memo.set(1, 1); returnaction1nmemo ← {0: 0, 1: 1}, action ← base 0; memo.set(0, 0); fib(2)=1; memo.set(2, 1)
8}9const value: number = fib(n - 1, memo) + fib(n - 2, memo);10memo.set(n, value);values this step{0: 0, 1: 1}memobase 0; memo.set(0, 0); fib(2)=1; memo.set(2, 1)action0nmemo ← {0: 0, 1: 1, 2: 1, 3: 2}, action ← hit 1; fib(3)=2; memo.set(3, 2)
8}9const value: number = fib(n - 1, memo) + fib(n - 2, memo);10memo.set(n, value);values this step{0: 0, 1: 1, 2: 1, 3: 2}memohit 1; fib(3)=2; memo.set(3, 2)action1nmemo ← {0: 0, 1: 1, 2: 1, 3: 2, 4: 3}, action ← hit 1; fib(4)=3; memo.set(4, 3)
8}9const value: number = fib(n - 1, memo) + fib(n - 2, memo);10memo.set(n, value);values this step{0: 0, 1: 1, 2: 1, 3: 2, 4: 3}memohit 1; fib(4)=3; memo.set(4, 3)action2nmemo ← {0: 0, 1: 1, 2: 1, 3: 2, 4: 3, 5: 5}, action ← hit 2; fib(5)=5; memo.set(5, 5)
8}9const value: number = fib(n - 1, memo) + fib(n - 2, memo);10memo.set(n, value);values this step{0: 0, 1: 1, 2: 1, 3: 2, 4: 3, 5: 5}memohit 2; fib(5)=5; memo.set(5, 5)action3nmemo ← {0: 0, 1: 1, 2: 1, 3: 2, 4: 3, 5: 5, 6: 8}, action ← hit 3; fib(6)=8; memo.set(6, 8)
8}9const value: number = fib(n - 1, memo) + fib(n - 2, memo);10memo.set(n, value);values this step{0: 0, 1: 1, 2: 1, 3: 2, 4: 3, 5: 5, 6: 8}memohit 3; fib(6)=8; memo.set(6, 8)action4nstdout ← 8
15const result: number = fib(6, memo);16console.log(result);17console.log(JSON.stringify(Object.fromEntries(memo)));values this step8stdout8result
Complexity
- Time: O(n) with memoization (vs. O(2^n) without)
- Space: O(n) memo + O(n) call stack
Implementation notes
- TypeScript:
const memo: Map<number, number> = new Map();passed explicitly tofib(n, memo). TheMap<number, number>annotation documents the key/value contract. - The replay shows the call stack on one side and the memo map on the other so memo writes and cache hits are visually distinct.