A branch of mathematics that attempts to prove stuff about computers.
Unfortunately, all software engineers already know the answer to the useful theorems though (except perhaps notably for cryptography), e.g. all programmers obviously know that iehter P != NP or that this is unprovable or some other "for all practical purposes practice P != NP", even though they don't have proof.
And 99% of their time, software engineers are not dealing with mathematically formulatable problems anyways, which is sad.
The only useful "computer science" subset every programmer ever needs to know is:
- for arrays: dynamic array vs linked list
- for associative array: binary search tree vs hash table. See also Heap vs Binary Search Tree (BST). No need to understand the algorithmic details of the hash function, the NSA has already done that for you.
- don't use Bubble sort for sorting
- you can't parse HTML with regular expressions: stackoverflow.com/questions/1732348/regex-match-open-tags-except-xhtml-self-contained-tags/1732454#1732454 because of formal language theory
Funnily, due to the formalization of mathematics, mathematics can be seen as a branch of computer science, just like computer science can be seen as a branch of Mathematics!
The algorithmically minded will have noticed that paging requires associative array (like Java
Map
of Python dict()
) abstract data structure where:- the keys are linear pages addresses, thus of integer type
- the values are physical page addresses, also of integer type
The single level paging scheme uses a simple array implementation of the associative array:and in C pseudo-code it looks like this:
- the keys are the array index
- this implementation is very fast in time
- but it is too inefficient in memory
linear_address[0] = physical_address_0
linear_address[1] = physical_address_1
linear_address[2] = physical_address_2
...
linear_address[2^20-1] = physical_address_N
But there another simple associative array implementation that overcomes the memory problem: an (unbalanced) k-ary tree.
A K-ary tree, is just like a binary tree, but with K children instead of 2.
Using a K-ary tree instead of an array implementation has the following trade-offs:
- it uses way less memory
- it is slower since we have to de-reference extra pointers
In C-pseudo code, a 2-level K-ary tree with and we have the following arrays:and it still contains
K = 2^10
looks like this:level0[0] = &level1_0[0]
level1_0[0] = physical_address_0_0
level1_0[1] = physical_address_0_1
...
level1_0[2^10-1] = physical_address_0_N
level0[1] = &level1_1[0]
level1_1[0] = physical_address_1_0
level1_1[1] = physical_address_1_1
...
level1_1[2^10-1] = physical_address_1_N
...
level0[N] = &level1_N[0]
level1_N[0] = physical_address_N_0
level1_N[1] = physical_address_N_1
...
level1_N[2^10-1] = physical_address_N_N
- one
directory
, which has2^10
elements. Each element contains a pointer to a page table array. - up to 2^10
pagetable
arrays. Each one has2^10
4 byte page entries.
2^10 * 2^10 = 2^20
possible keys.K-ary trees can save up a lot of space, because if we only have one key, then we only need the following arrays:
- one
directory
with 2^10 entries - one
pagetable
atdirectory[0]
with 2^10 entries - all other
directory[i]
are marked as invalid, don't point to anything, and we don't allocatepagetable
for them at all