A collection of coding challenge/interview problems solved in JavaScript. Oftentimes a single file will declare the same function more than once (e.g. ./freeCodeCamp/fibonacci.js); each subsequent definition is generally a more efficient version than what precedes it.

Also: solutions to (eventually) all exercises in Eloquent JavaScript.

Big Theta partial list of common functions in asymptotic notation, listed from slowest to fastest growing:

1. Θ(1)
2. Θ(lg n)
3. Θ(n)
4. Θ(n lg n)
5. Θ(n²)
6. Θ(n²​​ lg n)
7. Θ(n³)
8. Θ(2^n)

###Constant Growth

A function has constant growth if its output does not change based on the input, n.

###Logarithmic Growth

###Linear Growth

A function has linear growth if its output increases linearly with the size of its input. If n is never raised to a power greater than 1 or used as a power, it is linear, e.g. 3n.

###Linearithmic Growth

A function is linearithmic if we multiply linear terms by a logarithm, they take the form: n logK n. With n being equal in both, then the growth is dependent on the base k of the logarithms. Lesser bases grow more quickly than higher bases, so e.g. n log2 n will grow more quickly than n log6 n

###Polynomial Growth

A function has polynomial growth if its output increases according to a polynomial expression. The way to identify polynomial functions is to find those where n is raised to a constant power, e.g. 2n³ or 3n³.

###Exponential Growth

A function has exponential growth if its output increases according to an exponential expression. The way to identify exponential funcitons is to find those where a constant is raised to some expression involving n, e.g. 2^n or (3/2)^n.

###Debugger Steps:

• add a debugger statement in a function
• call the function manually
• $ node inspect index.js
• to continue execution of file, press 'c' then 'enter'
• to launch a repl session, type 'repl' then 'enter'
• to exit the repl, press Ctrl + C