Binary Search Tree Binary Search Trees
A binary search tree is a fundamental data structure useful for organizing large sets of data. It’s ideal whenever you need to retrieve and sort data quickly.
More on Wikipedia: http://en.wikipedia.org/wiki/Binary_search_tree
A binary tree is built from nodes. Each node has:
A) An element of data B) A link to the left. All nodes to the left have elements with a value less or lower than this node’s data element. C) A link to the right. All nodes to the right have elements with a value more or greater than this node’s data element. Base Expectations
Build a binary search tree which can fulfill each of the interactions below.
Assume we’ve started with:
tree = BinarySearchTree.new insert
The insert method adds a new node with the passed-in data. Each node is comprised of a score and a movie title. It returns the depth of the new node in the tree.
tree.insert(61, "Bill & Ted's Excellent Adventure")
tree.insert(16, "Johnny English")
tree.insert(92, "Sharknado 3")
tree.insert(50, "Hannibal Buress: Animal Furnace")
For all the later methods defined here, assume that we’ve run these four inserts.
include?
Verify/reject the presence of a score in the tree:
tree.include?(16)
tree.include?(72)
depth_of
Reports the depth of the tree where a score appears. Return nil if the score does not exist:
tree.depth_of(92)
tree.depth_of(50)
max
Which movie has the highest score in the list? What is it’s score?
tree.max
min
Which movie has the lowest score in the list? What is it’s score?
tree.min
sort
Return an array of all the movies and scores in sorted ascending order. Return them as an array of hashes. Note: you’re not using Ruby’s Array#sort. You’re traversing the tree.
tree.sort
load
Assuming we have a file named movies.txt with one score/movie pair per line:
34, Hannibal Buress: Comedy Camisado 63, Meet My Valentine 22, Experimenter 84, French Dirty 41, Love 10, I Love You Phillip Morris tree.load('movies.txt')
Where the return value is the number of movies inserted into the tree. If a score is already present in the tree when load is called, ignore it.
See an example file here
health
Report on the health of the tree by summarizing the number of child nodes (nodes beneath each node) at a given depth. For health, we’re worried about 3 values:
Score of the node Total number of child nodes including the current node Percentage of all the nodes that are this node or it’s children tree.insert(98, "Animals United") tree.insert(58, "Armageddon") tree.insert(36, "Bill & Ted's Bogus Journey") tree.insert(93, "Bill & Ted's Excellent Adventure") tree.insert(86, "Charlie's Angels") tree.insert(38, "Charlie's Country") tree.insert(69, "Collateral Damage") tree.health(0) => [[98, 7, 100]] tree.health(1) => [[58, 6, 85]] tree.health(2) => [[36, 2, 28], [93, 3, 42]] Where the return value is an Array with one nested array per node at that level. The nested array is:
[score in the node, 1 + number of child nodes, floored percentage of (1+children) over the total number of nodes] When the percentages of two nodes at the same level are dramatically different, like 28 and 42 above, then we know that this tree is starting to become unbalanced.
Understanding the Shape
This extensions is made up of two methods:
leaves
A leaf is a node that has no left or right value. How many leaf nodes are on the tree?
tree.leaves
height
What is the height (aka the maximum depth) of the tree?
tree.height