# 12.20 Study Log 3h Tonight I finished off the fibonacci memoization kata from last night and started on harvard’s cs50 class. The first one was super interesting and the instructor did a great job of explaining things that are difficult to come up with real world analogs for. I’m looking forward to the rest of the class. I’m not really looking forward to the coursework for this week as it is programming in scratch and I’m kind of pretentious about using simplified coding tools like that. I’m sure I’ll get through it though and we will then be on to python, c, php, and javascript.

Here is the writeup from my kata.

``````// https://www.codewars.com/kata/529adbf7533b761c560004e5/train/javascript
//
// Problem Context
// The Fibonacci sequence is traditionally used to explain tree recursion.
//
// function fibonacci(n) {
//     if(n==0 || n == 1)
//         return n;
//     return fibonacci(n-1) + fibonacci(n-2);
// }
// This algorithm serves welll its educative purpose but it's tremendously
// inefficient, not only because of recursion, but because we invoke the fibonacci
// function twice, and the right branch of recursion (i.e. fibonacci(n-2))
// recalculates all the Fibonacci numbers already calculated by the left branch
// (i.e. fibonacci(n-1)).
//
// This algorithm is so inefficient that the time to calculate any Fibonacci
// number over 50 is simply too much. You may go for a cup of coffee or go take a
// nap while you wait for the answer. But if you try it here in Code Wars you will
// most likely get a code timeout before any answers.
//
// For this particular Kata we want to implement the memoization solution. This
// will be cool because it will let us keep using the tree recursion algorithm while
// still keeping it sufficiently optimized to get an answer very rapidly.
//
// The trick of the memoized version is that we will keep a cache data structure
// (most likely an associative array) where we will store the Fibonacci numbers as
// we calculate them. When a Fibonacci number is calculated, we first look it up in
// the cache, if it's not there, we calculate it and put it in the cache, otherwise
// we returned the cached number.
//
// Refactor the function into a recursive Fibonacci function that using a memoized
// data structure avoids the deficiencies of tree recursion Can you make it so the
// memoization cache is private to this function?

// this was my initial passing code.
let memoStore = {};

let fib_lookup = function(fib){
if (memoStore[fib]) return memoStore[fib];
let new_fib = fibonacci(fib);
memoStore[fib] = new_fib;
return new_fib;
}

var fibonacci = function(n) {
if(n==0 || n == 1) return n; //recursion basecase
return fib_lookup(n-1) + fib_lookup(n-2);
}

//while writing this up I re-read the instructions and saw the line about keeping
// the memoized data private to the function. I rebuilt it into this by wrapping
// everything in another function. I'm not sure if that is the best way to do it,
// but it should all be private this way.

let fibonacci = function(fib) {
let memoStore = {};

let inner_fibonacci = function(n){
if(n==0 || n == 1) return n; //recursion basecase
return fib_lookup(n-1) + fib_lookup(n-2);
};

let fib_lookup = function(fib){
if (memoStore[fib]) return memoStore[fib];
let new_fib = inner_fibonacci(fib);
memoStore[fib] = new_fib;
return new_fib;
};

return fib_lookup(fib);
}

// this is when I submitted it for final and checked the other answers. It seems
// like mine worked as expected, but all of the top rated answers used IIFE for
// closure. I found this good page on IIFE and tried to refactor into using one
// of those.
// https://medium.com/@vvkchandra/essential-javascript-mastering-immediately-invoked-function-expressions-67791338ddc6
// but I couldn't get it quickly and I'm not 100% sure that it would even
// be an improvement.
``````

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