binary search tree – Data Science, Data Analytics and Machine Learning Consulting in Koblenz Germany https://www.rene-pickhardt.de Extract knowledge from your data and be ahead of your competition Tue, 17 Jul 2018 12:12:43 +0000 en-US hourly 1 https://wordpress.org/?v=4.9.6 balanced binary search trees exercise for algorithms and data structures class https://www.rene-pickhardt.de/balanced-binary-search-trees-exercise-for-algorithms-and-data-structures-class/ https://www.rene-pickhardt.de/balanced-binary-search-trees-exercise-for-algorithms-and-data-structures-class/#comments Tue, 29 Nov 2011 14:20:40 +0000 http://www.rene-pickhardt.de/?p=971 I created some exercises regarding binary search trees. This time there is no coding involved. My experience from teaching former classes is that many people have a hard time understanding why trees are usefull and what the dangers of these trees is. Therefor I have created some straight forward exercises that nevertheless involve some work and will hopefully help the students to better understand and internalize the concepts of binary search tress which are in my oppinion one of the most fundamental and important concepts in a class about algorithms and data structures.

Part A: finding elements in a binary search tree – 1 Point

You are given a binary search tree and you know the root element has the value 2. Considering that the path to for finding an element in the tree is unique decide which of the following two lists can be an actual traversal part in order to receive the element 363 from the binary search tree? Why so?

  • 2, 252, 401, 398, 330, 344, 397, 363
  • 2, 252, 397, 398, 330, 344, 401, 363

Part B: Create binary search trees – 1 Point

You are given an empty binary search tree and two lists of the same elements.

  • 10, 20, 5, 15, 2, 7, 23
  • 10, 5, 7, 2, 20, 23, 15

For both lists draw all the trees that are created while inserting one element after the other one.

Part C: skewed binary search trees and traversing trees – 1 Point

Compare the trees from part B to the tree you would get if inserting the numbers in the order of 2, 5, 7, 10, 15, 20, 23
To understand the different tree traversals please give the result of the inorder and preorder traversal applied to the trees from part B and C.

Part D: Balanced binary search trees. Counting Permutations – 2 Point

We realize that trees can have different topologies as soon as the order of the inserted items changes. Since balanced trees are most desired your task is to count how many permutations of our 7 elements will lead to a balanced binary search tree!
To do so it is sufficient to write down all the permutations that will lead to a balanced binary search tree. But you do not have to do this explicitly. It is also ok to write down all classes and cases of permuations and count them.
Compare the number to all permutations of 7 elements (= 7!) and give the probability to end up with a balanced binary search tree when given a random permutation of 7 different elements.

Part E: A closed formular for the probability to create a balanced binary search tree – 2 Extra Points

Your task is to find and prove a formular that states the number of permutations of the natural numbers 1, 2,…, 2^k-1 such that inserting the numbers will create a balanced binary search tree.
Give a closed forumlar for the probability P(k) to end up with a balanced search tree. Give the explicit results for k = 1,…,10

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