Counting Compares in HashSet

The assignment requires students to investigate the impact of a poor hash function on HashSet and repeat some experiments using this class. Students will create an application that adds sequences of items or BadItems (randomly generated positive odd values) to three sets: BinarySearchTreeArray, TreeSet, and HashSet. They will then count the number of comparisons required for successful and unsuccessful searches in each set, measure the heights of trees and the number of leaves in the array-based binary search tree, and plot the data against the size of the sets. Additionally, students are asked to modify the BinarySearchTreeArray class to implement the Serializable interface, test its serialization and deserialization capabilities, and report their findings.

Completing and Experimenting with the
BinarySearchTreeArray<E> class
Note that this coursework should be completed
individually. Unlike part A, there is relatively little
programming in this assignment and the main task is to
test and reflect on the relative performance of three Set
classes. Please read this project specification carefully
before starting the work.
It is intended to contribute to the assessment of the
following three learning outcomes:
L2. Design and develop implementations of collection
classes, applying the principles of object-oriented
programming and conforming to the relevant
conventions, standards and accepted best practice in the
programming language used.
L3. Identify and implement algorithms, using recursion
where appropriate, for a variety of technically demanding
tasks including explorations of graphs and search spaces
to find and/or arrive at a destination or goal state.
L4. Recognise the implications for type safety and the
guaranteeing of object invariants that arise when trying
to meet requirements for persistence, and in designing
classes for serialization and de- serialization take full
account of these.
Completing the BinarySearchTreeArray<E> class
You will have received detailed feedback on your
submission for part A. It is recommended that you go
through the comments you have received and the
published solution and make any corrections to your

BinarySearchTreeArray<E> class that are necessary to
address the points raised. At the end of this process you
should have a fully functional implementation of the
class, based on what you submitted for part A, that you
can use as the basis for part B of the coursework but, if
not, you may use the published solution for the
BinarySearchTreeArray<E> class as the basis for this
project.
Some Experiments with BSTs
This part of the coursework involves conducting some
experiments on binary search trees using the
BinarySearchTreeArray<E> class that was the subject
of part A of the project.
COMP09044 Cswk part B Page 1 Version 2.5
The Structure of the Trees
The binary tree theorem relates the number of elements
in a binary tree to the number of leaves in the tree and to
the height of the tree. The theorem states these
relationships to be:
leaves(t) <= (n(t) + 1)/2.0 <= 2height(t)
If t is a two-tree then leaves(t) equals (n(t) + 1)/2.0, if t is
full then (n(t) + 1)/2.0 equals 2height(t).
For sets implemented using the
BinarySearchTreeArray<E> class and the red-black tree
of the java.util.TreeSet<E> class, you will
explore how the number of elements in each set relates
to the height of the tree, and for the
BinarySearchTreeArray<E> class you will also explore

how the number of leaves in the tree relates to the
number of elements, in both cases using trees
constructed with sequences of randomly generated
positive integer values.
TreeSet<E> does not define a method to return the
height of its tree. This can be inferred, however, from the
number of comparisons required to find the element that
is most distant from the root, and this same approach can
be used to find the height of an instance of the
BinarySearchTreeArray<E> class. Here is a method,
using an Item class that counts comparisons (discussed
later in this project specification), that returns the height
of a binary search tree:
private static long height (Set<Item> tree) { long
maxComp = 0;
for (Item current : tree) { Item.resetCompCount();
tree.contains(current);if (maxComp <
Item.getCompCount()) {
maxComp = Item.getCompCount(); }
}
return maxComp-1; }
For the BinarySearchTreeArray<E> class to determine
the number of leaves you can add the following method
to your Entry<E> class
(this assumes you have declared a constant, equal to -1,
to represent a “null reference” – here this has been called
NIL):
COMP09044 Cswk part B Page 2 Version 2.5

public boolean isLeaf() {return left == NIL && right
== NIL;
}and the following methods to the
BinarySearchTreeArray<E>
class:
private int countLeaves(int nodeIndex) { if (nodeIndex
== NIL) return 0; Entry<E> node = tree[nodeIndex];
if (node.isLeaf()) return 1;
int count = countLeaves(node.left); count +=
countLeaves(node.right); return count;
}
protected int leaves() {
return countLeaves(root); }
Note that the countLeaves() method above is
recursive. You may prefer to use an iterative
implementation. In your report of the work, discuss
how it, and any recursive methods in the original
BinarySearchTree<E> class, could be implemented
iteratively, and whether for any of these methods
you did, in the final version of the
BinarySearchTreeArray<E> class for this assignment,
adopt an iterative or recursive implementation of
the methods.
The Performance of three Set classes in Searches
You will also investigate the number of comparisons
necessary to search for items in such trees and contrast
these with each other and with the comparisons required

for searching the hashtable Set<E> implementation in
java.util.HashSet<E>.
Finally, in terms of these experiments, you will
investigate the effect on how balanced the trees are, and
on the number of comparisons required for searching for
items, after large numbers of insertions and deletions
have been executed for the two tree classes.
To count the number of comparisons required when
performing operations on the Sets such as adding an
item, removing an item and searching for an item you
should write an application that uses the following class
(published in the Assignments area on Moodle) as the
element type for the three Set<E> classes:
COMP09044 Cswk part B Page 3 Version 2.5
import java.io.Serializable;public class Item implements
Comparable<Item>,
Serializable
{
/**
* Provides an immutable integer valued
item that
* counts comparisons.
*/
private static long compCount = 0;
private final Integer value;
/*** Constructor creates an Item and sets its
value * @param value the value for this Item*/
public Item(Integer value) {

this.value = value; }
/*** The value of this Item * @return the Item's
value */
public Integer value() { return value;
}
/**
* Compares the value of this Item with
that of
* other according to the contract for
Comparable.
* Increments the count of comparisons.
*/
@Overridepublic int compareTo(Item other) {
compCount++;
return value.compareTo(other.value); }
/*** Returns the total number of comparisons
performed * on instances of type Item since the
counter was * last reset (or the total if it has
never been+ reset).* @return the count of calls to
compareTo() and* equals for type Item*/
public static long getCompCount() {
return compCount; }
COMP09044 Cswk part B Page 4 Version 2.5
} }
compCount++;if (this == that) return true;if (!(that
instanceof Item)) return false; Item other =

(Item)that;return value.equals(other.value);
/**
* Resets the count of comparisons to zero.
*/
public static void resetCompCount() { compCount = 0;
}
@Overridepublic String toString() {
return value.toString(); }
@Overridepublic int hashCode() {
return value.hashCode(); }
@Overridepublic boolean equals(Object that) {
To use the Item class the basic approach is illustrated
below (where elements is a List<Item> containing the
list of items to search for,
in this case, where each search of the tree should
successfully find the item, having the same set of items
as the BinarySearchTreeArray<Item>, bst):
Item.resetCompCount();int errorCount = 0;for (Item
current : elements) {
if (!bst.contains(current)) errorCount++;
}long comparisonsBST = Item.getCompCount();
Item.resetCompCount();
To investigate the impact of a poor hashCode() function
on HashSet, repeat at least some of the experiments
using this class:

COMP09044 Cswk part B Page 5 Version 2.5
public class BadItem extends Item {
public BadItem(int value) { super(value);
}
@Overridepublic int hashCode() {
return super.hashCode() % 10; }
}
You will not need to change the declarations of the three
sets or any lists that you use (i.e. they can still be
declared as Set<Item> and List<Item>) to add
instances of BadItem to the collections as a BadItem is
an Item.
Note that the getEntry() method of HashSet<E>
compares the references to objects that have the same
hash code using the == operator and only calls the
equals() method of the objects if their hash code is the
same but the references to them are different. In testing
HashSet, therefore, you should ensure that a search does
involve a call of the equals() method of the Item being
searched for or the comparison will not be counted. This
can be achieved by ensuring that a successful search
involves using an Item with the same value as one in the
set, but does not involve using the actual instance of
Item that you added to the set as the parameter to
methods such as contains() or remove().
Outline of the Experiments
In your investigations you should write an application that

creates an instance of your BinarySearchTreeArray
class and also create an instance of java.util.TreeSet
and of java.util.HashSet. In all three cases, the
element type should be Item.
In your experiments, add the same sequence of Items, or
in the repeat, the same sequence of BadItems (using
randomly generated
positive odd values) to each of the three sets. Once the
sets have been built, determine the heights of the trees
for the two tree- based sets and the number of leaves in
your binary search tree class. Count the number of
comparisons required to find all of the Items in each set.
Search the three sets for the same number of even
valued Items (or BadItems), so that each search is
unsuccessful, and again count the number of
comparisons that are
COMP09044 Cswk part B Page 6 Version 2.5
required (e.g. for sets of size 15, say, search for 15 even
values that fall within the same overall range of values as
the values added to the sets).
Repeat these experiments with different numbers of
elements, across a good range of sizes (up to at least
tens of thousands). Plot the heights of the trees and the
number of leaves in the array- based binary search tree
against the size of the trees. Also plot average number of
comparisons required for the successful and unsuccessful
searches against the size of the sets. You can use an
application such as Excel to plot the data (in the first lab,
we produced comma-delimited files that Excel could
directly open, you may wish to do this). In your report,

discuss the results in the light of the binary tree theorem
and the extent to which they confirmed or otherwise what
you expected to find.
To explore how binary search trees perform over
time, you should investigate and comment on the
effect, if any, on the structure of the trees after
large numbers of insertions and deletions have
been performed on each of the tree-based sets –
once you have filled the set keep the average size of the
set over the experiment roughly constant. That is, keep
the overall number of deletions and insertions roughly
equal – for example you might delete a fifth of the
elements, then add the same number of elements (not
the same values that you deleted but randomly
generated values) repeating this, say, 10 times and then
measure the heights of the trees and the number of
leaves again. Is any difference in the average number of
comparisons when searching for items observed after
such deletions and insertions, compared with what you
found in the initial experiments? Discuss whether you
expect the trees to become progressively more
unbalanced over time as items are removed and new
items added and whether your observations confirmed
this expectation. For these experiments, you need not
repeat the runs with BadItem, as the focus is on the two
tree-based sets.
You will receive credit for devising any additional
experiments or measures to complement those asked for
above in helping to interpret them, possibly involving
adding more protected methods to the
BinarySearchTreeArray<E> class additional to those
required for the Set<E> interface. For example (but these

are by no means the only possibilities), you might
investigate performance when items are not added in
random sequence but in ascending or descending order.
Or it might be useful to provide a method to calculate the
external path length of the tree and relate this to the
comparison counts you obtained when searching for
items and/or to
COMP09044 Cswk part B Page 7 Version 2.5
the external path length theorem we discussed in the
lecture on binary trees.
Making the BinarySearchTreeArray<E> class
serializable
Modify the BinarySearchTreeArray<E> class so that it
implements the Serializable interface. Test that
instances of the tree can be
serialized to file and successfully recreated from file. You
should refer to the notes in the Serialization subpage on
Moodle for information on how to update a class to be
serializable while making it tolerant to version changes
and ensuring that the runtime and serialized forms of the
type are only loosely coupled. You may assume that any
element type for the tree implements Serializable (as
does the Item class above).
Reporting your results
Produce and submit an individual report on the work
covering the experimental results and how the type was
updated to be serializable. You should include a critical
appraisal of your work. Note that the report must be
included. For parts of the task that involve your

comparing things and discussing things (such as the
recursive and iterative implementation of
countLeaves()), the comparison and the discussion
should be included in the report.
Summary and Marking Scheme
1. Part B (Weighted at 30% of module marks)
a. Write an application to investigate the properties and
performance of the BinarySearchTreeArray class
and of TreeSet and HashSet as outlined above. [25
marks]
b. Amend the BinarySearchTreeArray class so that
instances of the class can be serialized and
deserialized. Marks will be based on this successfully
working and on the extent to which the type controls
its serialization so that the runtime and serialized
forms of the type are only loosely coupled. [25
marks]
c. A report including presentation and discussion of
experimental method and results, discussion of use
of recursion, summary of how you implemented
serialization, and a critical appraisal of the work. [50
marks]
Note that, as with part A, you must include an
acknowledgement in your report for any sources you
have used (on the web, textbooks etc) in developing or
commenting on design, code and in your testing, and any
source code used from sources other than the
COMP09044 Cswk part B Page 8 Version 2.5

course textbook should be indicated in the code by a
comment at the beginning and end of the code stating
the source from which it was taken. If you receive any
advice from anyone you should acknowledge this also
and indicate what part of the work it related to. You
should not share any of the application code (i.e. your
program to run the experiments on the three Set
classes), or the code for serializing the array-based tree
class, that you produce with anyone.