COMP3210/6210: Assignment 2
Semester 1, 2021
Department of Computing
Macquarie University
Marks: 100 marks (20%)
Due Date: 11:59 PM, 04 June 2021 (Friday, End of Week 13)
What to Submit: Source code, a recorded video, and a report
Where to Submit: Electronic submission via iLearn
This is an individual coding assignment. The objective is to implement the R-tree. Each submission
will be graded based on correctness. The rest of the document explains the details.
How Your Submission Will Be Tested:
[Dataset]: You will be given a dataset that contains 2D points. The dataset will be provided in
a text file as the following format:
id 1 x 1 y 1
id 2 x 2 y 2
...
id n x n y n
Every line gives a point’s id, x-, and y-coordinates. Your program should build an R-tree in
memory from the dataset.
[Range Query]: You will be given a set of 100 range queries in a text file whose format is:
x 1 x’ 1 y 1 y’ 1
x 2 x’ 2 y 2 y’ 2
...
x 100 x’ 100 y 100 y’ 100
That is, each line specifies a query whose rectangle is [x, x′] × [y, y′]. Then, we will measure its
query efficiency as follows.
You should output to a disk file:
• Firstly, your program should display the time of answering queries by reading the entire
dataset sequentially. This time serves as the sequential-scan benchmark to be compared
with the cost of your query algorithms that leverage the R-tree.
• Secondly, display the number of points returned by each query-note: we need only the
number of points retrieved , instead of the details of those points.
• Thirdly, display the total running time of answering all the 100 queries, and the average
time of each query (i.e., divide the total running time by 100).
[Programming Language]: Python, Java, C++ (including variants like C, C#, ...), or any other
language approved by the instructor. You can implement the R-tree by using the existing libraries
provided in the programming language of your choice (i.e., some standard libraries or the libraries
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for R-Tree).
[Deliverables]: Your submission includes the following components:
1. Source Code: The code you have developed yourself. Make sure your code can be run in
the standard general programming environment.
2. Report: Your report should include the following:
• A brief description of the main functions in your source code.
• A clear specification of the requirements for executing your code such as, OS environ-
ment, placement of input files, any input parameters, etc.
• A detailed analysis for the construction and search of an R-Tree.
3. A Recorded Video: You need to prepare for a recorded video to show the process of
running your program, the delivered results, and a brief introduction of how did you design
your program.
4. Zip all your source code and the recorded video into a single file , and name the file
in the following format: yourstudentid surname.zip. You need to submit your zip file
and your report separately via the submission system.
Marking: Your total mark earned for this assignment is based on:
• [The Program: 60 marks]
– Correctness: 40 marks.
∗ [Sequential-Scan Based Method (10 marks)]: You need to provide detailed
comments for your source code (2 marks). Then, if your program correctly answers
m (out of 100) queries by reading the entire dataset (reading all the data points)
sequentially, you get 8 · (m/100) marks for this part.
∗ [R-Tree Based Method (30 marks)]: You need to provide detailed comments
for your source code (5 marks). Then, if your program correctly answers m (out of
100) queries by searching the R-Tree, you get 25 · (m/100) marks for this part.
– Efficiency: 10 marks. If the average query time is at least 5 times faster than the
sequential scan, you get 10 marks for this part. If at least 2 times faster (but less than
5 times), you get 5 marks. If less than 2 times faster, no marks.
– Recorded Video: 10 marks. The video should clearly show the process of running
your program (2 marks), show the delivered results (2 marks), and clearly introduce
your idea in the design of your program to show your understanding of implementing
the R-Tree (6 marks).
• [The Report: 40 marks]
– Function Description: 5 marks. If your report includes a clear description of all
the functions in your source code, you get 5 marks. If only part of your functions is
introduced, you will be given the marks based on the proportion of the correct answers.
– Requirement Description: 5 marks. If your report includes a clear description
of the requirements for executing your code such as, OS environment, placement of
input files, any input parameters, etc, and your report includes the screenshots of the
running results (e.g., the average execution time of both sequential-scan and R-Tree
based methods, etc.), you get 5 marks.
– Analysing the Working of R-Tree: 30 marks. Select no less than 10 data points
from the given dataset, and one query from the given queries. You need to draw figures
to illustrate the whole process of R-Tree construction (20 marks) and the R-Tree based
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search (10 marks). The search should traverse several nodes of the tree, and during the
construction of the R-Tree, there should be an overflow and a node splitting.
Late Submission: No extensions will be granted without an approved application for Special
Consideration. There will be a deduction of 10% of the total available marks (10 marks for the
assignment, scale to 2 marks in your final grade) made from the total awarded mark for each 24
hour period or part thereof that the submission is late. For example, 25 hours late in submission
for this assignment– 20% penalty (20 marks deducted, scale to 4 marks in your final grade). No
submission will be accepted after the solutions have been posted.
Zero Tolerance for Cheating: You are required to develop the program and write the report by
yourself. If you use some libraries and/or contents from other sources, you need to cite and provide
the corresponding references. All submissions will be checked for plagiarism . Any confirmed
cases will be reported to the faculty for disciplinary actions, and the marks of the assignment and
the unit will be held until the case has been resolved. See Macquarie University’s code of conduct
for the details of the process. https://students.mq.edu.au/study/getting-started/student-conduct
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