Fundamentals of Programming
COMP1005 Assignment
Discipline of Computing
Curtin University
1 Preamble
In practicals you have implemented and learned about simulations, object-orientation and
(soon) how to automate the running of multiple simulations. In this assignment, you will be
making use of this knowledge to extend a given simulation to provide more functionality,
complexity and allow automation. You will then report on your design and implementation, and
the results generated by the simulation.
2 The Challenge
You will be simulating the behaviour and interaction of one or more puppies/dogs. The yard
the dogs live in consists of grassed area, garden, fences, gates and house. We will view it
from above. Your simulation will include dogs/puppies (multiple types possible), squirrels (a
major distraction), humans (various types), yard/house (sectioned by surface and
accessibility), toys and food sources, and senses (sight, smell and sound). This will be
plotted as a top-view of the activities. The model can be assumed flat/2-D – there may be
bonus marks for 3D, but not required.
We will provide some sample code to start this assignment, and additional code showing a
range of approaches to assignments from previous semesters. For the assignment, you will
develop code to model the dogs using objects, and to add features to the simulation (e.g. food,
toys, humans and interactions). Your task is to extend the code and then showcase your
simulation, varying input parameters, to show how they impact the overall simulation.
Note: You do not have to use the supplied sample code, however, any other code that you
have not written (e.g. sourced from others, online or generated etc.) will not receive marks.
Lecture/practical and test materials from COMP1005/5005 are exempt, however they must be
referenced.
Remember : Think before you code!
You can do a lot of the assignment planning on paper before any coding. The Feature
column of the Traceability Matrix should be filled in before coding, then used as a guide and
checklist as you work through the assignment.
The assessable features for snoo.py are: 2
1. Animals: Represented as objects that “know” their position, name, colour and age
and can strategise on their next activity. You should have at least Dogs/Puppies and
Squirrels
Prompts: How will you represent the animals themselves, and differentiate between
them in the simulation? How will they move and decide between movement options?
Will they get hungry/thirsty/lonely/bored?
2. Humans: Humans will have varying relationships with the Animals. Some will be
owners/friends, some strangers/intruders. Humans will bring food and may play with
the dog(s).
Prompts: How will you differentiate the humans? How will the dog sense the types of
humans? Will there be a regularity of interaction, e.g. feed/play at certain times?
3. Food Sources/Toys: The main food sources for the dogs are given by humans. Your
animals should have a value for energy/hunger that is increased by eating and
decreases over time. Food sources should deplete as they are eaten. Toys can be
played with and moved from place to place. Items may be buried, then found via smell.
Prompts: How will the animals find and respond to food sources? How will you track
energy and the food source(s) being eaten? How will a toy be “carried”?
4. Senses: Each creature will have a way of sensing the world around them. You should
have sight and smell as a starting point, then potentially add hearing.
Prompts: How will you code the “sight” of the animals? Many aspects of the simulation
will have a smell, which may be in a trail that fades over time. You might do this as a
parallel grid... Which senses/events will take priority?
5. Terrain and Obstacles: There should be at least two types of area in the terrain –
back yard and house. Different animals will traverse their terrains in their own manner,
although within a class they should have the same patterns. Obstacles might be
fences, walls or doors/gates. These can be built in the code, however they will be better
if read from a file.
Prompts: How will the animal know what terrain it is in? How will this affect their choice
of movement for each time step? How will they get around obstacles?
6. Collisions/Interaction: How will your creatures seek out or avoid each other? They
will need to detect each other and take action, with a decision being made on the
outcome of any interactions.
Prompts: How will you detect a collision is imminent? What strategies will you have
for the animals to avoid each other?
There are marks allocated for flexibility and usability. For example, changing terrain input
file, or numbers of dogs/humans/squirrels/food can give very different simulations. You can
begin with hard-coded values and filenames, but should move to prompting for values, or a
better approach is to use command line arguments to control the parameters of the
experiment/simulation. Configuration files can also be used.
Your code should include comments to explain what each section does and how. Apply PEP8
and other style guides throughout - this will affect your readability score in our marking.
Also beware of using while/True, break, continue and global variables – these are all
discouraged in the unit – even if you see examples of their use online.
It may be useful to keep track of your progress/changes in the comments at the top of the
program. Feel free to re-use the code and approaches from the lectures and practicals.
However, remember to cite/self-cite your sources. If you submit work that you have already
submitted for a previous assessment (in this unit or any other) you must specifically state this.
Beyond the working program, you will submit a document: the Project Report, worth 40% of
the assignment marks. This is described in Section 3.1. 3
There will be bonus marks for additional functionality and the use of more advanced
programming techniques (e.g. interactivity, high quality visualisation, 3D space, parameter
sweep etc.) but only if they are sensible and done well. Make sure to discuss the additional
work in your Report, this will be easy if you make notes and keep old (incremental) versions
of your code.
3 Submission
Submit electronically via Blackboard. You can submit multiple times – we will only mark the
last attempt. This can save you from disasters! Take care not to submit your last version late
though. Read the submission instructions very carefully.
You should submit a single file, which should be zipped (.zip). Check that you can decompress
it successfully. The submission file must be named FOP_Assignment_<id> where the <id> is
replaced by your student id. There should be no spaces in the file name; use underscores as
shown.
The file must contain the following:
• Code – snoo.py and supporting files, i.e. all files needed to run your program,
including input files.
• README file including short descriptions of all files and dependencies, and
information on how to run the program.
• Report for your code, as described in Section 3.1.
• Cover Sheet - signed and dated. These are available on Blackboard. You can sign a
hard copy and scan it in or you can fill in a soft copy and digitally sign it.
• You will also need to submit the Report to TurnItIn.
Make sure that your zip file contains what is required. Anything not included in your zip
submission will not be marked. It is your responsibility to make sure that your submission is
complete and correct – submitted to the main assignment link as a single zip file.
3.1 Project Report
You need to submit your Report in Word doc or pdf format. You will need to describe how
you approached the implementation of the simulation, and explain to users how to run the
program. You will then showcase the application(s) you have developed, and use them to
explore the simulation outputs. This exploration would include changing parameters,
simulation time and perhaps comparing outcomes if you switch various features on/off.
THE REPORT MUST BE SUBMITTED THROUGH TURNITIN AND IN THE ZIP FILE
Your Project Report will be around 10 pages and should include the following:
1. Overview (2 marks) describe your program's purpose and implemented features.
2. User Guide (2 marks) how to use your simulation (and parameter sweep code, if
applicable)
3. Traceability Matrix (10 marks) of features, implementation and testing of your code.
The matrix should be a table with columns for:
i. Feature - numbered for easy referencing
ii. Code reference(s) – reference to files/classes/methods or snippets of
code only, do not put the whole program in the report
iii. Test reference(s) – test code or describe how you tested your feature
was correctly implemented
iv. Completion date - N/A if not implemented 4
4. Discussion (10 marks) of implemented features (referring to the Traceability Matrix),
explaining how they work and how you implemented them. A UML Class Diagram
should be included for objects and their relationships.
5. Showcase (10 marks) of codeoutput, including three different scenarios:
a. Introduction: (4 marks) Describe how you have chosen to set up and compare
the simulations for the showcase. Include commands, input files – anything
needed to reproduce your results.
b. Discussion: (3x2 marks) Show and discuss each scenario’s outputs/results.
6. Conclusion (2 marks) reflection on your assignment with respect to the specification
7. Future Work (2 marks) further investigations and/or extensions that could follow.
8. References (2 marks)
A report template is available on Blackboard.
3.2 Marking
Marks will be awarded to your submission as follows:
• [30 marks] Code Features. Based on your implementation and documentation
• [30 marks] Demonstration. Students will demonstrate their code and respond to
questions from the markers. Marks are assigned for each feature implemented
and for the usability and flexibility of the code.
• [40 marks] Project Report. As described in section 3.1.
Marks will be deducted for not following specifications outlined in this document, which
includes incorrect submission format and content.
3.3 Requirements for passing the unit
Please note: As specified in the unit outline, it is necessary to have attempted the
assignment in order to pass the unit. As a guide, your assignment must score at least 15%
(before penalties) to be considered to have attempted this assignment. We have given you
the mark breakdown in Section 3.2. Note that the marks indicated in this section represent
maximums, achieved only if you completely satisfy the requirements of the relevant section.
Plagiarism is a serious offence. This assignment has many correct solutions so plagiarism will
be easy for us to detect (and we will). For information about plagiarism, please refer to
http://academicintegrity.curtin.edu.au.
You will be asked to explain parts of your code and the reason for choices that you have made
during the demonstration. A failure to display knowledge required to have produced the code
will most likely result in being formally accused of cheating.
Finally, be sure to secure your code. If someone else gets access to your code (e.g. because
you left it on a lab machine, lost a USB drive containing the code or put it on a public repository)
you will be held partially responsible for any plagiarism that results.
3.4 Late Submission
As specified in the unit outline, you must submit the assignment on the due date. If there are
reasons you cannot submit on time, you should apply formally for an Assessment Extension.
If you submit your assignment late (without an extension), you will be penalised based on the
number of days it is late.
Students with a Curtin Access Plan should include a submission note to indicate the extra
time they have taken, ensuring they have submitted the CAP to Blackboard for us to check. 5
3.5 Clarifications and Amendments
This assignment specification may be clarified and/or amended at any time. Such clarifications
and amendments will be announced in the lecture and on the unit’s Blackboard page. These
clarifications and amendments form part of the assignment specification and may include
things that affect mark allocations or specific tasks. It is your responsibility to be aware of
these, either by attending the lectures, watching the iLecture and/or monitoring the Blackboard
page.
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