Prepping for a Google Interview

These are a bunch of notes I took when I was reading through Cracking the Coding Interview in prep for a Google Interview

• spelling algorithms correctly is important

peaks

• insertion sort always O(N^2) because going through and moving
• binary sort can assist it to be O(log(n)n) for insertions but still N^2 for swaps
• merge sort two arrays, sort, then merge, then split and repeat. O(log(n)n) complexity
• priority queue - - maxheap, nodes are always larger than or equal to their children (max heap property) - minheap, nodes are always smaller than or equal to their children (min heap property)
• heap sort – heap on a tree, (breadth first view,) int array[7]; indexies -AVL trees
  • traverse = n
  • insert nlog(n)
  • delete min
  • find next min and max and next smaller and next min
  • log(n),

Comparison Model -Searching: (lng) -Sorting nln(n) -All input items are blackboxes In reality

Linear time sorting for not large - O(n sqrt(lnln(n)) -Prehashing = alpha = n/m time, orderone = theta(1+alpha) (a*k)mod(2^w) » 2^(r-w) where m = 2^r also k mod m - hash the function and modulus

Hash table properties

• make use of all info provided by key (Key:Value)
• uniformly distrutes output across table
• maps similar keys to very different hash values
• uses only very fast operations to minimize run time.

TODO

• Binary Tree / n-tree / AVL Tree / tr-tree
  • Their Traversals
  • Insert/delete/search
• Make Graph / Search / Edges/Vertices
• Quick/MergeSort