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Python Problem Solver: Identify a problem and code your solution
Overview As you might have noticed through the previous assignments, algorithms can be used to solve many of the daily problems to make life easier. In this assignment, you will showcase what you learned during the course. You are now equipped with strong problem-solving tools that can be applied to many problems. You will identify a problem that one might face and solve it through algorithmic thinking and Python implementation. The problem could be at any scale, starting from simple problems that you might be facing (like budgeting or sleeping cycles). You should find an appropriate level of challenge for your problem: be sure that you can implement a solution to the problem in code while showcasing your strengths in coding that you have developed over the course of this semester.
PART 1: Algorithm Description
Identify the problem clearly and then, using at least four LOs, devise an algorithm that can solve it. You should start with a very simple problem; you can always add features to your solution.
Describe your algorithmic approach
Describe the input(s), output(s) and the process of the algorithm
Draw a flowchart to show the process of the algorithm
Explain how this process is an algorithm
PART 2: Implementation
Using an appropriate data structure (Lists or any other data structure that you are familiar with) build a user-friendly Python program that practically implements your algorithm.
Provide a well-commented Python implementation for your algorithm.
Make sure to include few test-cases to make sure your code works
NOTES:
Be sure to comment thoroughly so that it is clear that you understand what every line of the code is intended to accomplish.
Include your test cases in your submission. Explain how you used these test cases in your comments.
Learning Outcomes Added
computationaltools: Apply the computational terminology and tools appropriately in different quantitative contexts.
algorithmicstrategies: Demonstrate the ability to think logically and systematically about problems, breaking them down into a clear, ordered set of concrete steps that could be implemented by a machine.
compprogramdesign: Generate working programs in a computer language that can solve computational problems; find and fix bugs that appear in them.
quantcommunication: Communicate with a clear and precise style that is suited to an appropriate audience. Produce code that can be easily read and understood by others.
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