<p> Properties of various ADTs</p><p>1. LIST</p><p> a. can be accessed from front, middle, and end</p><p> b. to search for an item:</p><p> i. if not sorted: </p><p> it has to be a sequential search. O(n)</p><p> for items not in the list: you have to search until the end</p><p> ii. if sorted: </p><p> and if it is implemented as an array or vector it can be searched using binary search. O(log n)</p><p> if searched sequentially and item not in the list you can stop once you passed the place where the item should be, you do not have to search until the end.</p><p> c. adding to a sorted list requires finding appropriate location</p><p>2. STACK</p><p> a. additions and removals are done at one end … the TOP</p><p> b. you access the last (newest) item added first (LIFO)</p><p> c. you can not add in the middle of a stack</p><p>3. QUEUE</p><p> a. additions are done at the END of the queue</p><p> b. removals are done at the FRONT of the queue</p><p> c. you access the first (oldest) item added first (FIFO) d. you can not add in the middle of a queue</p><p>4. PRIORITY QUEUE (PQ)</p><p> a. it is a variation of a queue that is sorted by priority</p><p> b. additions are done in specific positions according to priority</p><p>(not controlled by user, it is controlled by the ADT)</p><p> c. removals are done at the FRONT of the PQ, just like a regular queue</p><p> d. you can access the most important item first, that is the item with the highest priority.</p><p> e. Do NOT confuse with sorted list. Here you can only remove from front!!</p><p>5. DEQUE</p><p> a. it is a combination of stack and a queue</p><p> b. you can add and remove from both ends</p><p> c. but you can not add or remove from the middle</p><p>6. BINARY SEARCH TREE (BST)</p><p> a. if traversed inorder produces sorted output</p><p> b. additions are easy, only need to find appropriate location by deciding left or right repeatedly (or recursively)</p><p> c. removals have different cases depending on whether the node to be removed is a leaf, has one child, or two children, so it is a little bit complicated.</p><p> d. search is of O(h) and h=height is at best O(log n) where n=number of nodes. This means the shorter the tree the faster the search. e. it is suitable for applications that require fast searching.</p><p>7. AVL TREE</p><p> a. a special kind of BST : </p><p> it is balanced, which means it is always shortest possible  faster search</p><p> b. additions are complicated, because need to keep tree balanced</p><p> c. removals are also complicated</p><p> d. not suitable if there are a lot of additions and removals all the time</p><p>8. B-TREE</p><p> a. another kind of balanced trees, but not a binary tree</p><p> b. used for huge amount of data</p><p>9. HEAP</p><p> a. a special kind of Binary Trees, but not a binary search tree</p><p> b. it is a complete binary tree</p><p> c. can be used to implement priority queues</p><p> d. can be used to sort data</p><p> e. additions are controlled by the ADT</p><p> f. removals always from root</p><p> g. Two kinds i. MAX heaps: </p><p> largest value in root and its subtrees are also max heaps ii. MIN heaps:</p><p> smallest value in root and its subtrees are also min heaps</p>