Data Structures for Midterm 2

C++ Data Structure Runtimes

vector Continuous memory Requires resize when capacity is exceeded Can push_back in O(1) General insert is O(n) due to shifting data O(1) lookup if index is known O(n) find – O(log(n)) if sorted using binary search

Linked List Non-continuous memory – Each data element contains a pointer to the memory location of the next element Used for stack and queue – O(1) for push, pop, top, queue, dequeue, front, back O(n) time to find even if the “index” is known – Don’t know where in memory the next the element is Can insert and delete in O(1) with pointer manipulation given an iterator to the proper location – stack and queue only use the ends of the list to get O(1) operations

Balanced Binary Tree Used for set and map Uses (key, value) with elements sorted by key – For set: key = value Searching a binary tree takes O(h) time – if the tree is balanced: h = O(log(n)) Insert and delete in O(1) with pointer manipulation, but must find the location first in O(log(n)) – Also takes O(log(n)) to balance the tree multiset and multimap retain duplicates

Hash Table Takes more time to adjust parameters – Hash function – Size of table – Implementation of bins Once set up, O(1) insert, find, and delete are achievable *Theoretically these operations are all O(n) – Practically they are O(1) – We will consider them to be O(1) in this class