PROG2007讲解 、辅导 Python设计程序
            
                Assessment Brief
PROG2007 PROGRAMMING II
Summary
Title Assessment 3
Due Date Tuesday 22 April 11:59 pm AEST/AEDT (start of Week 7)
Length NA
Weighting 20%
Academic 
Integrity
(See below for 
limits of use 
where GenAI is 
permitted)
GenAI May be used for this assessment. 
Please see the Academic Integrity section below for acceptable use of 
GenAI in this assessment.
Submission Please see the Submission section below on how to submit your 
assessment.
Unit Learning 
Outcomes 
This assessment task maps to the following ULOs:
ULO2: design, implement, test, and debug simple programs in an 
object-oriented programming language.
ULO3: demonstrate how to use class mechanisms to support 
encapsulation and efficient code.
ULO4: analyse and determine appropriate data structures and 
iteration methods to support a solution.
Rationale
By integrating improvements in error handling, messaging, and testing into their codebase, 
developers can enhance the overall quality and resilience of the Python bot. These 
enhancements not only contribute to a smoother user experience but also bolster the code's 
reliability and maintainability in the face of evolving requirements and challenges.
Task Description 
You have 24 hours to complete the tasks based on improvement of your Assessment 2 solution. 
You apply the concepts covered in Module 6 of this unit to demonstrate more advanced use of 
exceptions and testing.
Task Instructions 
Choose one (1) of the classes from your Assessment 2 submission that is best suited for the 
following tasks. 
1. Create a new file FirstName_LastName_A3.py and copy and paste the chosen class into it
2. Update the class to demonstrate your:
a. use of the raise keyword using built-in exceptions where appropriate.
b. use of a custom exceptions using the raise keyword where appropriately
3. Pick one of the methods in your class to test and create a new file to demonstrate:
a. a comprehensive testing approach using pytest
b. create a series of tests to ensure there are no possible errors left unhandled.
c. all tests must be in a file called FirstName_LastName_A3_Testing.py
Resources
Everything that you need to know to complete this assessment was covered in Module 6 of this 
unit.
Task Submission
You can use PyCharm or VSCode to complete the assignment and your assignment must run 
using Python 3. This is covered in the Getting Started section of MySCU.
The submission requirements are as follows:
• Your submission must be named as follows FirstName_LastName_A3.py and 
FirstName_LastName_A3_Testing.py . For example:
o Alex_Hendry_A3.py
o Alex_Hendry_A3_Testing.py
• You are only required to submit your Python files and not your project files.
• You are required to use the WakaTime plugin and submit a screenshot of your 
WakaTime dashboard when submitting your assignment clearly identifying how much 
time you spent on each part of the assessment. 
Please note that the file naming instructions in this assignment must be followed EXACTLY, 
including the file names you are instructed to use. Failure to do so may result a requirement to 
resubmit. 
Academic Integrity
At Southern Cross University, academic integrity means behaving with the values of honesty, 
fairness, trustworthiness, courage, responsibility and respect in relation to academic work.
The Southern Cross University Academic Integrity Framework aims to develop a holistic, 
systematic and consistent approach to addressing academic integrity across the entire 
University. For more information, see: SCU Academic Integrity Framework
NOTE: Academic Integrity breaches include unacceptable use of generative artificial intelligence 
(GenAI) tools, the use of GenAI has not been appropriately acknowledged or is beyond the 
acceptable limit as defined in the Assessment, poor referencing, not identifying direct 
quotations correctly, close paraphrasing, plagiarism, recycling, misrepresentation, collusion, 
cheating, contract cheating, fabricating information. 
Use of GenAI
There are no limitations on using GenAI in this assignment providing you follow the following 
guidelines:
• You understand the code you are submitting and can explain it.
• You are not using any concepts that are not taught in the unit. 
• All code that was created using GenAI must be clearly identified using a comment. The 
following are possible examples of comments you may use:
o This method was created using GenAI.
o This block of code was partly created using GenAI.
o This constructor was generated using ChatGPT.
• Your code runs without errors.
If your submission is deemed to be suspicious by your marker you may be asked to attend an 
interview in your tutorial class to explain your code. If you cannot explain your code, you may 
be submitted for academic integrity. Possible reasons your submission may be deemed 
suspicious could include:
• Using programming concepts not taught in the unit.
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• Using programming concepts considered by your marker to be beyond your 
programming abilities as demonstrated in the class.
• Submitting code suspected of being generated using GenAI software but is not clearly 
identified.
To summarise:
• You can use GenAI as much as you like as long as you clearly identify the code you submit 
and understand what it does. 
• DO NOT SUBMIT ANY CODE THAT YOU DO NOT UNDERSTAND AND CANNOT EXPLAIN.
Collusion
Please note that your source code for this assignment will be run through a plagiarism detection 
system designed for code that compares all assignments and highlights identical or very similar
submissions. If you are found to have colluded with other students, you will be submitted for 
academic integrity.
Special Consideration
Please refer to the Special Consideration section of Policy.
https://policies.scu.edu.au/document/view-current.php?id=140
Late Submissions & Penalties
Please refer to the Late Submission & Penalties section of Policy.
https://policies.scu.edu.au/view.current.php?id=00255
Grades & Feedback
Assessments that have been submitted by the due date will receive an SCU grade. Grades and 
feedback will be posted to the ‘Grades and Feedback’ section on the Blackboard unit site. Please 
allow 7 days for marks to be posted.
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Assessment Rubric
Marking Criteria and 
% allocation
High Distinction
(85–100%)
Distinction
(75–84%)
Credit
(65–74%)
Pass
(50–64%)
Fail
(0–49%)
Error handling and 
validation strategies
50%
Applies comprehensive error 
handling and validation 
strategies, ensuring robust 
program resilience and 
flawless handling of all 
potential exceptions.
Applies effective error 
handling and validation 
strategies, significantly 
enhancing program 
stability and effectively 
managing most exceptions.
Adequately applies error 
handling and validation 
strategies, maintaining 
program stability and 
addressing common 
exceptions appropriately.
Applies basic error 
handling and validation 
strategies, covering 
essential exceptions and 
maintaining minimal 
program continuity.
Fails to apply effective 
error handling and 
validation strategies, 
resulting in program 
instability and inadequate 
management of exceptions.
Class and Method 
Testing
50% 
Tests the class method 
comprehensively using 
pytest, covering all scenarios 
and edge cases with 
meticulous attention to 
detail. Ensures all possible 
errors are handled, 
demonstrating a thorough 
understanding of error 
scenarios and effective error 
handling mechanisms.
Implements testing with 
pytest to validate the class 
method, but may overlook 
some edge cases.
Addresses most common 
errors but may miss 
handling less common 
scenarios.
Utilizes pytest for testing 
the class method, covering 
common scenarios 
adequately.
Shows understanding of 
error handling but may 
lack depth in addressing 
less common cases.
Attempts testing with 
pytest but lacks 
thoroughness, potentially 
missing important 
scenarios.
Basic error handling is 
present but may overlook 
significant cases.
Fails to adequately test the 
class method, leaving 
critical scenarios 
unhandled.
Lacks effective error 
handling, increasing the 
risk of program failures.
Description of SCU Grades
High Distinction:
The student’s performance, in addition to satisfying all of the basic learning requirements, demonstrates distinctive insight and ability in researching, analysing and 
applying relevant skills and concepts, and shows exceptional ability to synthesise, integrate and evaluate knowledge. The student’s performance could be described 
as outstanding in relation to the learning requirements specified.
Distinction:
The student’s performance, in addition to satisfying all of the basic learning requirements, demonstrates distinctive insight and ability in researching, analysing and 
applying relevant skills and concepts, and shows a well-developed ability to synthesise, integrate and evaluate knowledge. The student’s performance could be 
described as distinguished in relation to the learning requirements specified.
Credit:
The student’s performance, in addition to satisfying all of the basic learning requirements specified, demonstrates insight and ability in researching, analysing and 
applying relevant skills and concepts. The student’s performance could be described as competent in relation to the learning requirements specified.
Pass: 
The student’s performance satisfies all of the basic learning requirements specified and provides a sound basis for proceeding to higher-level studies in the subject 
area. The student’s performance could be described as satisfactory in relation to the learning requirements specified.
Fail: 
The student’s performance fails to satisfy the learning requirements specified.
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