LATE SUBMISSION PENALTY: 10% penalty per day. Submissions more than 7 calendar days late will receive 0. The number of days late is rounded up, e.g. 5 hours late
means. 1 day late, 27 hours late is 2 days late. For special consideration, please visit this page: https:/ /f orms . monash . edu/special- consideration and fill out the appropriate
PROGRAMMING CRITERIA: It is required that you implement this exercise strictly using the Python programming language (version should not be earlier than 3.5). This practical work will be marked on the time complexity, space complexity and functionality of your program, and your documentation.
Your program will be tested using automated test scripts. It is therefore critically important that you name your files and functions as specified in this document. If you do not, it will make your submission difficult to mark, and you will be penalised.
SUBMISSION REQUIREMENT: You will submit a single python file, assignment1 . py.
PL AGIARISM: The assignments will be checked for plagiarism using an advanced plagiarism detector. In previous semesters, many students were detected by the plagiarism detector and almost all got zero mark for the assignment and, as a result, many failed the unit. Helping others to solve the assignment is NOT ACCEPTED. Please do not share .your solutions partially or completely to others. If someone asks you for help, ask them to .visit a consultation for help.
This assignment achieves the Learning Outcomes of:
●1) Analyse general problem solving stra tegies and algorithmic paradigms, and apply them to solving new problenns;
●2) Prove correctness of programs, analyse their space and time complexities;
●3) Compare and contrast various abstract data types and use them appropriately;
●4) Develop and implement algorithms to solve computational problems.In addition, you will develop the following employability skills:
●Designing test cases. .
●Ability to follow specifications precisely.
In order to be successful in this assessment, the following steps are provided as a suggestion.
This is an approach which will be useful to you both in future units, and in industry.
1. Read the assignment specification as soon as possible and write out a list of questions you have about it.
2. Clarify these questions. You can go to a consultation, talk to your tutor, discuss the tasks with friends or ask in the forums.
3. As soon as possible, start thinking about the problems in the assignment.
●It is strongly recommended that you do not write code until you have a solid feeling for how the problem works and how you will solve it.
4. Writing down small examples and solving them by hand is an excellent tool for coming to a better understanding of the problem.
●As you are doing this, you will also get a feel for the kinds of edge cases your code . will have to deal with.
5. Write down a high-level description of the algorithm you will use.
6. Determine the complexity of your algorithm idea, ensuring it meets the requirements.
1. Think of test cases that you can use to check if your algorithm works.
●Use the edge cases you found during the previous phase to inspire your test cases.
●It is also a good idea to generate large random test cases.
●Sharing test cases is allowed, as it is not helping solve the assignment.
2. Code up your algorithm ( remember decomposition and comments), and test it on the tests you have thought of.
3. Try to break your code. Think of what kinds of inputs you could be presented with which your code might not be able to handle.
●Inputs with strange properties
●What if everything is the same?
●What if everything is different?
●Make sure that the input/output format of your code matches the specification.
●Make sure your filenames match the specification.
●Make sure your functions are named correctly and take the correct inputs.
●Make sure you zip your files correctly (if required).
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