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日期:2022-05-04 09:50


Coursework 3 Task Specification

Thomas Selig

Set: Saturday, 30 April, 2022

Due date: Sunday, 22 May, 2022, 10pm

This is the specification task sheet for the Coursework 3 assessment component of your CPT206

module. The task covers all Learning Outcomes, and has a weighting of 70% towards the final

grade for this module. This assignment has two parts: a coding part described in Section 1, and a

report described in Section 2. The submission deadline for this assignment is Sunday, 22 May,

2022, at 10pm. Detailed submission instructions are provided in Section 3.

1 Program description (65 marks)

The aim of this coursework is to build a program to store, manipulate, and retrieve information

from the evolution of stock prices over time. All the work should be coded into a single Java

NetBeans project, with the class structure and different functionalities of the program described as

follows. All classes should be properly encapsulated, as seen in the Lectures and Labs throughout

the semester. Your project should also contain a Controller class for testing.

1.1 PricePoint class (10 marks)

The basic building block of the program will be a simple PricePoint data class. A PricePoint

object comprises of a pair (t, p(t)), where t is a time coordinate, and p(t) the price at time t.

PricePoint objects should be compared according to their time coordinate.

1.2 PriceData class (25 marks)

A PriceData object stores a collection of PricePoint objects. You should choose a suitable data

structure in the Java collection framework for this, according to the following conditions.

? There should be no duplicate time coordinates among the PricePoint objects in the collection.

? The collection should be maintained in increasing order of time coordinates.

Leave a comment in your code explaining your choice of data structure for this.

In addition, your PriceData class should have the following functionalities.

1. It should be possible to create either an empty PriceData object ( containing no PricePoint

objects), or a customised object according to a specified (Java) Collection of PricePoint

objects.

1

2. There should be a method add(PricePoint newPp) to add a new PricePoint to a PriceData

object.

3. We can view a PriceData object as a function p : t 7→ p(t), where we take the linear

interpolation between any consecutive time coordinates of PricePoints. Let ti and tf be the

first and last time coordinates in a givenPriceData object. In addition to being able to get

the value p(t) of this linear interpolation for any time coordinate t ∈ [ti, tf ], it should be

possible to calculate the following statistics:

? the spread of the PriceData, given by max

t∈[ti,tf ]

(p(t))? min

t∈[ti,tf ]

(p(t));

? the average of the PriceData, given by

∫ tf

ti p(t) dt;

? the maximal differential of the PriceData, given by max

t1,t2∈[ti,tf ]

∣∣∣∣p(t1)? p(t2)t1 ? t2

∣∣∣∣.

Each of these should be implemented through a method with the same name as the statistic in

question (e.g. spread() for the spread statistic). There should also be a general display()

method in the PriceData class which displays the above statistics over the given time period

in a sensible and informative manner.

1.3 StockPriceData class (15 marks)

Finally, a StockPriceData object should be a PriceData object with the additional information

of the name of the stock, and two coefficients:

? a positive volatility coefficient v;

? a probability pi ∈ [0, 1] measuring how likely price trends are to continue.

The StockPriceData class should have the same functionalities as the PriceData class. In addition,

there should be a method that, given a time differential ?t, estimates a future PricePoint for the

stock, as follows.

? Draw a random variable r ∈ [0, v].

? Let ε ∈ {?1,+1} be the monotinicity of p(t) at t?f , that is ε = +1 if the function p(t) is

increasing in the final time interval, and ε = ?1 otherwise. Then the future PricePoint is

given by the pair

(

tf + ?t, p(tf + ?t)

)

, where

p(tf + ?t) =

{

p(tf )(1 + εr?t) with probability pi

p(tf )(1? εr?t) with probability (1? pi)

.

1.4 Code quality (15 marks)

The remaining marks (15) will be awarded for the quality of your code, as covered throughout the

semester in the Lectures and Labs.

? Keep your code neat and tidy; make sure it is properly indented throughout.

? Choose suitable names for variables and methods, respecting standard Java naming conventions.

? Comment your code as needed.

? Split your code into separate methods as appropriate; methods should not be too long.

2

2 Report (35 marks)

For this part of the assignment, you will write a report detailing how you designed, implemented,

and tested the program described in Section 1. The report should be typed into e.g. a Word

document, and submitted as a PDF (see Section 3 for more details).

2.1 OOP features (10 marks)

Over the course of the semester, you have learned a number of OOP features (e.g. encapsulation)

and principles (e.g. single responsibility principle). In your report, you will explain where you

have incorporated these in your design and how you have done so; include a brief definition of

the features/principles in question. Be as precise as possible, illustrating with small portions of

code if necessary. Note that not all the features and principles we saw in the lectures need to be

incorporated into your design; your report should only discuss those that are. This section should

be one-and-a-half to two pages in length.

Good example: The Single Responsibility Principle states that every class in the program

should have responsibility over a single functionality of the program; a class should do one thing.

This principle is incorporated into our class design: all the classes have their own, separate, purpose.

For instance, the PricePoint class1...

Bad example: Encapsulation and inheritance are two core features of OOP; they are used in

many parts in my program.

2.2 Testing description (15 marks)

As covered throughout the Lectures and Lab sessions in this module, testing is an essential part of

writing computer programs. In your report, you will include a description of how you tested the

various parts of the program described in Section 1. You will state clearly what functionalities you

tested, and describe how you tested them, thinking carefully about possible corner cases. You may

include some sample code if you wish. This section should be one-and-a-half to two pages in length

(screenshots excluded).

2.3 Improvements (10 marks)

Finally, this program is, by necessity, a simplified model. In your critical evaluation document,

you will list two (2) possible improvements to the system. These could be for instance additional

features to be implemented, changes to existing features so that the system is a more accurate

reflection of a real-world system, etc. Give a brief justification for why these would improve the

system. This part should be no longer than one page in length.

1Give a brief description of the purpose of the PricePoint class here.

3

3 Submission instructions

In the dedicated “Coursework 3 submission” Assignment activity on the Learning Mall Online, you

will need to submit the following two (2) documents.

? A single ZIP archive of your entire NetBeans project. Include all the resources your

project needs to run. This file will be named “CPT206 CW3 Project studentId.zip”.

? Your report from Section 2, typed into e.g. a Word document, and converted into a PDF

file. This file will be named “CPT206 CW3 Report studentId.pdf”.

The submission deadline is: Sunday, 22 May, 2022, at 10pm.

This assignment is individual work. Plagiarism (e.g. copying materials from other sources

without proper acknowledgement) is a serious academic offence. Plagiarism and collusion will not

be tolerated and will be dealt with in accordance with the University Code of Practice on Academic

Integrity. Submitting work created by others, whether paid for or not, is a serious offence, and

will be prosecuted vigorously. Individual students may be invited to explain parts of their code in

person during a dedicated BBB session, and if they fail to demonstrate an understanding of the

code, no credit will be given for that part of the code.

Late submissions. The standard University policy on late submissions will apply: 5% of

the total marks available for the component shall be deducted from the assessment mark for each

working day after the submission date, up to a maximum of five working days, so long as this does

not reduce the mark below the pass mark (40%); submissions more than five working days late will

not be accepted.

This is intended to be a challenging task, and quite a step up from what you have been doing

so far, so think about things carefully. We can - and will - discuss some aspects in the Lab sessions,

and of course, as usual, you can ask me anything by email, during Office Hours, or in the LMO

Forums. Good luck!


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