# ps3 - CS2020 Data Structures and Algorithms(Accelerated...

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CS2020: Data Structures and Algorithms (Accelerated) Problems 5–6 Due: February 2nd, 13:59 Overview. You have two tasks this week. The ﬁrst involves implementing a basic binary search tree. In another problem set later this semester, you will improve your search tree so that it always remains balanced (using a new weight-balancing technique diﬀerent from that seen in class). The second task involves using a balanced search tree to implement an airport scheduling system. Collaboration Policy. As always, you are encouraged to work with other students on solving these problems. However, you must write up your solution by yourself . In addition, when you write up your solution, you must list the names of every collaborator, that is, every other person that you talked to about the problem (even if you only discussed it brieﬂy). Any deviation from this policy will be considered cheating, and will be punished severely, including referral to the NUS Board of Discipline. 1

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Problem 5. Basic Binary Search Trees For this question, your task is to implement a basic binary search tree in Java. Notably, your search tree must satisfy the binary search tree property: every key in a node’s left sub-tree must be smaller than the key stored at the node itself, and every key in a node’s right sub-tree must be larger than the key stored at the node itself. Inserting an element into the tree and searching for an element in the tree should take time O ( h ), where h is the height of the tree. Your solution to this problem set should consist of a class which implements the ITreeNode interface distributed with the problem set. A tree node should contain a key, along with a reference to its parent (if any), its left child (if any) and its right child (if any). The ITreeNode interface contains the following methods: getLeftChild , getRightChild , getParent : returns the left child, the right child, or the parent (or null, if the speciﬁed child/parent does not exist). getWeight : returns the total number of keys stored in the sub-tree rooted at the tree node (see below) getKey : returns the key associated with the tree node getTreeKeys : returns a sorted list of every key in the sub-tree rooted at the tree node insert : inserts an integer into the sub-tree rooted at the tree node search : queries whether a given integer appears in the sub-tree rooted at the tree node Each of these functions should be implemented as eﬃciently as possible. Notice that one of the required functions returns the weight of a node. We deﬁne the weight of a tree node as the total number of keys that are stored in that sub-tree. For example, the weight of a leaf node is 1. In general, the weight of a node v is equal to: v.left.weight + v.right.weight + 1 (where we deﬁne v.left.weight = 0 if v has no left child, and v.right.weight = 0 if v has no right child). While the weight can be re-calculated on every call to getWeight , that can be quite expensive (costing O
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ps3 - CS2020 Data Structures and Algorithms(Accelerated...

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