# Draw a diagram of the tree resulting from setting the root to be BinaryTreeNode(“a”), and subsequently using the add method to add “b”, “c”, “d”, “e”, “f”, “g” to the root in that order.

Binary Trees
Consider the BinaryTreeNode class shown below. public class
BinaryTreeNode {
public Object element;
public BinaryTreeNode left;
public BinaryTreeNode right;
public BinaryTreeNode(Object element) {
this.element = element;
this.left = null;
this.right = null;
}
BinaryTreeNode node = new BinaryTreeNode(element); if (left == null)
left = node;
else if (right == null) right = node;
else if (left.size() < right.size())
}
public int size() {
int size = 1;
if (left != null) size += left.size();
if (right != null) size += right.size();
return size;
} }
(a) Draw a diagram of the tree resulting from setting the root to be
“c”, “d”, “e”, “f”, “g” to the root in that order.
2. (b) Taking into account that both size() and add() are implemented
recursively and that add() calls size(), derive an informal estimate of the
time complexity for the add() method.
3. (c) Consider how you might improve the efficiency of the add() and
size() methods with respect to time by storing the size as an attribute of
the class. Explain your new design and detail the changes you would make to
the BinaryTreeNode class and its methods.
4. (d) Explain whether the changes you have made in part (c) above alter the
time complexity of the add() method. If not, why not, if so, what is the new
time complexity and why.
3. Grammars and parsing
1. (a) Grammar descriptions often include “one or more” and “zero or more”
patterns. Give an example of a grammar containing a “one or more” pattern,
and show how the same pattern can be implemented using explicit recursion.
What does this result suggest to you: Is this extra syntax needed? Why? (Or
why not?)
2. (b) Consider the following fragment of a grammar for a Java-like language:
method = mod type IDENTIFIER OPEN args CLOSE
block
mod = visibility STATIC?
visibility = PUBLIC | PROTECTED | PRIVATE
args = type IDENTIFIER (COMMA args)?
(where symbols in CAPITALS denote terminals). Explain how you would
implement a parser for this grammar using recursive descent. Illustrate your
answer using pseudo-code to implement the method and args
productions. (You may assume that you already have recogniser functions for
all the other symbols, and can create any additional functions you need.)
3. (c) Suppose you now decided to implement terminal recognisers directly
from the string representing the program text, rather than performing
tokenisation to get a stream of tokens. How would you go about it? How
would you keep track of “where you are” in parsing the input? What would
the terminal recognisers look like (in pseudocode)?
4. Graphs, complexity, and data structure management
1. (a) One of the major pitfalls in designing algorithms such as breadth-first
traverses that operate on graphs is ensuring that they always terminate.
Explain (with an example) how this problem arises, and explain in detail how
to ensure that a traverse of graphs avoids divergence.
2. (b) Dijkstra’s algorithm works by storing a distance for each node in the
graph. Compare and contrast the following two approaches to representing
the distance:
1. (i) As an attribute on the class representing nodes; and
2. (ii) As a lookup table mapping node labels to distances.
Explain carefully any assumptions you make and any restrictions that you
need to impose.
3. (c) Suppose you decide to use the adjacency matrix representation of a
graph. Discuss the issues that arise when adding nodes to the graph using
this representation. What is the computational complexity of this operation in
terms of the number of nodes N? Discuss a technique to improve the
performance of the operation, and compare and contrast the costs involved
with those of the edge list representation.

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