Computational Problem Solving

4COM2005/10 Computational Problem Solving

Programming Exercise

Weighting: This assignment is worth 30% of the marks for the module

Authorship: This is an Individual Assignment. You must work on your own.

Number of hours you are expected to work: It should take about 4 hours to complete

Due to the nature of the assignment and the proximity of the marking deadline late submissions cannot be accepted without a Short-Term Extension agreed before the start of the assignment.

Task 1 (20 marks) is to implement a set of functions that operate on / produce data structures
You are provided with a set of function specifications in the skeleton Python script task1.py, which contains a series of incomplete function definitions and some instructions and a tester program, along with a test plan for the functions, and a PDF of a Venn diagram for use with function 1

Task 2 (10 marks) is to implement / modify a Python class
You are provided with a set of specifications for the class coin_game in the Python script task2.py along with a program that uses the class and some instructions on what to do

There is no Task 3

Submission Requirements:

Upload a zip archive containing modified copies of the two Python scripts task1.py and task2.py to Canvas. Make sure you have inserted your SRN where required by the instructions given in each script.

Marks will be awarded for program correctness

Each correctly implemented function / method you provide is worth a different number of marks).

  • The functions will be tested by an automated system
    • If your code for a task fails to run due to a syntax error the automated tester will award 0 marks for the whole task
    • If a function returns an incorrect result for one or more the tests the automated tester wil award 0 marks for those tests
    • If a function crashes your program when tested with data that it should be able to handle the automated tester will award 0 marks for those tests
  • Automated testing will be backed up by human inspection

Module Learning Outcomes assessed (from Definitive Module Document)

On completion of the module successful students will have a knowledge and understanding of
• how discrete structures, including self-similar structures, may be represented and manipulated in Python..
In addition, successful students will typically be able to:
• write Python programs that solve well-specified problems
• choose appropriate data structures and make judicious use of recursion and iteration to manipulate them.

Additional information:
• Regulations governing assessment offences including Plagiarism and Collusion are available from https://www.herts.ac.uk/__data/assets/pdf_file/0007/237625/AS14-Apx3-Academic-Misconduct.pdf (UPR AS14).
• Guidance on avoiding plagiarism can be found here: https://herts.instructure.com/courses/61421/pages/referencing-avoidingplagiarism?
module_item_id=779436

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