Algorithms and data structures FIT2004
FIT2004 2024 Semester 1: Assignment 1
DEADLINE: Friday 26th April 2024 23:55:00 AEST.
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 seconds
late means 1 day late, 27 hours late is 2 days late.
For special consideration, please visit the following page and fill out the appropriate form:
https://forms.monash.edu/special-consideration.
The deadlines in this unit are strict, last minute submissions are at your own risk.
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 impor-
tant 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 containing all
of the questions you have answered, assignment1.py. Moodle will not accept submissions
of other file types.https://weibo.com/u/7916053997
PLAGIARISM: The assignments will be checked for plagiarism using an advanced pla-
giarism detector. In previous semesters, many students were detected by the plagiarism
detector and almost all got zero mark for the assignment (or even zero marks for the unit as
penalty) and, as a result, the large majority of those students failed the unit. Helping others
to solve the assignment is NOT ACCEPTED. Please do not share your solutions partially
or completely to others. Even after the deadline, your solutions/approaches should not be
marks that are possibly assigned for that part of the task as it is not your own work).
The use of generative AI and similar tools for the completion of your assignment
is not allowed in this unit!
1
DEADLINE: Friday 26th April 2024 23:55:00 AEST.
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 seconds
late means 1 day late, 27 hours late is 2 days late.
For special consideration, please visit the following page and fill out the appropriate form:
https://forms.monash.edu/special-consideration.
The deadlines in this unit are strict, last minute submissions are at your own risk.
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 impor-
tant 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 containing all
of the questions you have answered, assignment1.py. Moodle will not accept submissions
of other file types.https://weibo.com/u/7916053997
PLAGIARISM: The assignments will be checked for plagiarism using an advanced pla-
giarism detector. In previous semesters, many students were detected by the plagiarism
detector and almost all got zero mark for the assignment (or even zero marks for the unit as
penalty) and, as a result, the large majority of those students failed the unit. Helping others
to solve the assignment is NOT ACCEPTED. Please do not share your solutions partially
or completely to others. Even after the deadline, your solutions/approaches should not be
shared before the grades and feedback are released by the teaching team. Using content
from the Internet, books etc withou t citing is plagiarism (if you use such content as part
of your solution and properly cite it, it is not plagiarism; but you wouldn’t be getting anymarks that are possibly assigned for that part of the task as it is not your own work).
The use of generative AI and similar tools for the completion of your assignment
is not allowed in this unit!
1
