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Estimates the time difference in performance for recursive and iterative function in javascript. Using finabocci as a case study
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recurse :: (Integral a) -> a -> a | |
recurse 1 = 1 | |
recurse 0 = 1 | |
recurse n = recurse (n-2) + recurse (n-1) | |
-- refactoring | |
recurse :: (Integral a) -> a -> a | |
recurse n | |
| n < 2 = 1 | |
| otherwise = recurse (n-2) + recurse (n-1) |
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function recurse(n) { | |
if (n < 2) return 1; | |
return recurse(n - 2) + recurse(n - 1); | |
} | |
// O(fib(n)) = O(φ^n) (φ = (1+√5)/2); | |
function iterate(n) { | |
if(n <= 1) { | |
return n; | |
} | |
var fib = 1; | |
var prevFib = 1; | |
for(var i=1; i<n; i++) { | |
var temp = fib; | |
fib+= prevFib; | |
prevFib = temp; | |
} | |
return fib; | |
} | |
function memoizedRecurse() { | |
memoizedValue = {}; | |
return function recurse(n){ | |
if(memoizedValue[n]) return memoizedValue[n]; | |
if (n < 2) return 1; | |
f = recurse(n - 2) + recurse(n - 1); | |
memoizedValue[n] = f; | |
return f; | |
} | |
} | |
function perf(times, func, msg) { | |
const start = Date.now(); | |
for (let i = 0; i <= times; ++i) { | |
func(); | |
} | |
console.log(msg, 'Time taken to complete:', Date.now() - start, 'ms'); | |
} | |
x = memoizedRecurse() | |
perf(10000000, () => recurse(10), 'Recursion'); | |
perf(10000000, () => iterate(10), 'Iterative'); | |
perf(10000000, () => x(10), 'memoizedRecursion'); |
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You can simpy run the code on any browser to figure that out