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Final Programming Project
General Instructions
In this project, you will solve THREE dependent programming tasks and write a short README
document which briefly introduces your code and logic in each task. We will grade your
submission manually with reference to your program logic, so there is generally no input/output
requirement. You should implement and test the program by following questions in each task. You
can use whatever programming language you like in this project, but we encourage you to use
C/C++ or Python, as we had multiple practices over them.
Total: 100 points
30 points for the first program
30 points for the second program
30 points for the third program
10 points for your document
Submission
1. The deadline will be announced in Moodle. Late submission will not be accepted.
2. You will receive 0 marks if you submit after the deadline.
3. You will receive 0 marks if you submit incorrect files.
4. You should compress your code (3) and document (1) into a ZIP/TAR file, and submit only ONE
compressed file.
Evaluation
We will review your work individually to ensure that you receive due credit for your work. Please
note that both your program output and logic will be considered for marking.
Academic Dishonesty
We will check your code against other submissions in the class and from the Internet for logical
redundancy. If you copy someone else’s code and submit it with minor changes, we will know. We
trust you all to submit your own work only; please don’t let us down. If you do, we will pursue the
strongest consequences available to us.
About the project
As we have introduced several programming technologies, in this final project, you are going to
learn, develop and optimize an advanced and useful data structure – Binary Search Tree (BST).
BST stores "items" (such as numbers, names etc.) in computer memory. It allows fast lookup,
addition and removal of items. You will need to understand the operations of BST through on-line
sources (e.g., Google, Github) and implement them according to our requirements.
Here are some links for useful information in this project:
1. https://en.wikipedia.org/wiki/Binary_search_tree
2. https://en.wikipedia.org/wiki/AVL_tree
3. https://www.cnblogs.com/lordage/p/6031616.html?from=timeline&isappinstalled=0
4. https://hackernoon.com/learn-c-multi-threading-in-5-minutes-8b881c92941f
5. https://www.tutorialspoint.com/cplusplus/cpp_multithreading.htm
Task 1 BST( 30 points)
Hospital A’s database records patients’ identities and their ages. Here is a sequence of
pairs: <3, 10>, <1, 20>, <4, 17>, <6, 31>, <7, 17>, <13, 9>, <8, 25>, <10, 11>, <14, 28>. A binary
search tree has organized them into:
Figure 1. Sample Binary Search Tree
The id of each pair acts as the key in each node. For example, the root node of this tree is 8, which
represents the pair <8, 25>. Now you have to code for three operations of BST: addition, removal
and searching for a node. Please make sure you have understood how BST works and then start
your coding.
Q1. Implement the BST data structure and write three functions named insert(), remove() and
search() which correspond to the three functions.
Q2. Initialize the BST as showed in Figure 1. Then, call function insert() to add two nodes whose
pair are: <2, 49>, <0, 33> to this tree, respectively.
Q2. Call function remove() to delete node 7 in the tree while keeping the nodes in sorted order.
Q3. Call function search() to query the age of the patient whose identity is 13.
Task 2 AVL Tree( 30 points)
Binary Search Tree greatly decreases the searching time in large database since it leverages the idea
of binary search (refer to https://en.wikipedia.org/wiki/Binary_search_algorithm for details),
which is useful in many cases. For example, if you play a game to quickly guess a specific number
ranging from 1 ~ 100, it is best to first guess number 50, and then decide whether to guess 25 or 75
based on whether 50 is smaller or larger, and so on. However, binary search tree is not always
efficient. Consider the unbalanced binary search tree below, the height of the left subtree is 3 while
the right one is 1.
Figure 2. unbalanced binary search tree
If we search for the value whose key is 3, then the binary search algorithm retrogrades to linear
search in all data. To be more specific, in the worst case of a search in a binary search tree, the
performance could degrade greatly. The AVL tree figures out this problem by balancing the height
of subtrees for each node. Details of AVL tree can be found in above link 2 and 3.
Q1. Point out all the unbalanced trees below. (Write your answer to README document)
(a) (b) (c)
Q2. After executing all the questions in task 1 (Q1 ~ Q3), is the binary search tree balanced or not?
(Write your answer to README document)
Q3. If the binary search tree in Q2 is unbalanced, write a function rebalance () to rebalance the tree
after each operation by using the AVL algorithm. As there are many approaches to make it
balanced (e.g., RR, LL), please indicate your chosen approach clearly in the README document.
Task 3 Concurrent Search( 30 points)
As a balanced binary search tree, AVL tree has better performance in extreme cases (e.g., Figure 2).
In other word, AVL is an optimized version of BST which accelerates the searching process. In this
task, you are going to write a multi-thread version of BST, which also accelerates searching.
Multithreading is the ability of a CPU (or a single core in a multi-core processor) to provide
multiple threads of execution concurrently, supported by the operating system. All the programs
you write in this class are the single-thread program, which means that they use only limited
computation power of a computer. Thus, by using multi-thread search in a binary search tree, the
efficiency gets better.
Before programming, you will need to learn the multithreading technique by yourself (e.g., you
may refer to link 4 and 5 for some help).
Q1 (the only question in this task): Write a program that conducts a concurrent preorder traversal
of the BST of task 1 (after executed Q1 ~ Q3), and outputs
1. the result of preorder traversal (i.e., a list of node identities ).
2. the age of a patient whose identity is 6.
About preorder traversal: https://en.wikipedia.org/wiki/Tree_traversal
Hint:
1. You may use a thread pool. In each program run, assign the left subtree to a thread, and assign
the right subtree to a free thread in pool (if any). Otherwise, the thread itself deals with the
searching.
2. An unbalanced binary search tree may make the multi-threading program ineffective because
there will always be one thread dealing with a long subtree while another thread only deals with a
very short tree (see Figure 2), you have to design to make thread assignment fair. (You do not need
to consider the case, however, it’s a plus for making.)
Important
Remember to write a README document that briefly introduce your code in each task and how to
run them (e.g., environment, command). Also, you have to answer some of the questions in your
README.
Final Programming Project
General Instructions
In this project, you will solve THREE dependent programming tasks and write a short README
document which briefly introduces your code and logic in each task. We will grade your
submission manually with reference to your program logic, so there is generally no input/output
requirement. You should implement and test the program by following questions in each task. You
can use whatever programming language you like in this project, but we encourage you to use
C/C++ or Python, as we had multiple practices over them.
Total: 100 points
30 points for the first program
30 points for the second program
30 points for the third program
10 points for your document
Submission
1. The deadline will be announced in Moodle. Late submission will not be accepted.
2. You will receive 0 marks if you submit after the deadline.
3. You will receive 0 marks if you submit incorrect files.
4. You should compress your code (3) and document (1) into a ZIP/TAR file, and submit only ONE
compressed file.
Evaluation
We will review your work individually to ensure that you receive due credit for your work. Please
note that both your program output and logic will be considered for marking.
Academic Dishonesty
We will check your code against other submissions in the class and from the Internet for logical
redundancy. If you copy someone else’s code and submit it with minor changes, we will know. We
trust you all to submit your own work only; please don’t let us down. If you do, we will pursue the
strongest consequences available to us.
About the project
As we have introduced several programming technologies, in this final project, you are going to
learn, develop and optimize an advanced and useful data structure – Binary Search Tree (BST).
BST stores "items" (such as numbers, names etc.) in computer memory. It allows fast lookup,
addition and removal of items. You will need to understand the operations of BST through on-line
sources (e.g., Google, Github) and implement them according to our requirements.
Here are some links for useful information in this project:
1. https://en.wikipedia.org/wiki/Binary_search_tree
2. https://en.wikipedia.org/wiki/AVL_tree
3. https://www.cnblogs.com/lordage/p/6031616.html?from=timeline&isappinstalled=0
4. https://hackernoon.com/learn-c-multi-threading-in-5-minutes-8b881c92941f
5. https://www.tutorialspoint.com/cplusplus/cpp_multithreading.htm
Task 1 BST( 30 points)
Hospital A’s database records patients’ identities and their ages. Here is a sequence of
pairs: <3, 10>, <1, 20>, <4, 17>, <6, 31>, <7, 17>, <13, 9>, <8, 25>, <10, 11>, <14, 28>. A binary
search tree has organized them into:
Figure 1. Sample Binary Search Tree
The id of each pair acts as the key in each node. For example, the root node of this tree is 8, which
represents the pair <8, 25>. Now you have to code for three operations of BST: addition, removal
and searching for a node. Please make sure you have understood how BST works and then start
your coding.
Q1. Implement the BST data structure and write three functions named insert(), remove() and
search() which correspond to the three functions.
Q2. Initialize the BST as showed in Figure 1. Then, call function insert() to add two nodes whose
Q2. Call function remove() to delete node 7 in the tree while keeping the nodes in sorted order.
Q3. Call function search() to query the age of the patient whose identity is 13.
Task 2 AVL Tree( 30 points)
Binary Search Tree greatly decreases the searching time in large database since it leverages the idea
of binary search (refer to https://en.wikipedia.org/wiki/Binary_search_algorithm for details),
which is useful in many cases. For example, if you play a game to quickly guess a specific number
ranging from 1 ~ 100, it is best to first guess number 50, and then decide whether to guess 25 or 75
based on whether 50 is smaller or larger, and so on. However, binary search tree is not always
efficient. Consider the unbalanced binary search tree below, the height of the left subtree is 3 while
the right one is 1.
Figure 2. unbalanced binary search tree
If we search for the value whose key is 3, then the binary search algorithm retrogrades to linear
search in all data. To be more specific, in the worst case of a search in a binary search tree, the
performance could degrade greatly. The AVL tree figures out this problem by balancing the height
of subtrees for each node. Details of AVL tree can be found in above link 2 and 3.
Q1. Point out all the unbalanced trees below. (Write your answer to README document)
(a) (b) (c)
Q2. After executing all the questions in task 1 (Q1 ~ Q3), is the binary search tree balanced or not?
(Write your answer to README document)
Q3. If the binary search tree in Q2 is unbalanced, write a function rebalance () to rebalance the tree
after each operation by using the AVL algorithm. As there are many approaches to make it
balanced (e.g., RR, LL), please indicate your chosen approach clearly in the README document.
Task 3 Concurrent Search( 30 points)
As a balanced binary search tree, AVL tree has better performance in extreme cases (e.g., Figure 2).
In other word, AVL is an optimized version of BST which accelerates the searching process. In this
task, you are going to write a multi-thread version of BST, which also accelerates searching.
Multithreading is the ability of a CPU (or a single core in a multi-core processor) to provide
multiple threads of execution concurrently, supported by the operating system. All the programs
you write in this class are the single-thread program, which means that they use only limited
computation power of a computer. Thus, by using multi-thread search in a binary search tree, the
efficiency gets better.
Before programming, you will need to learn the multithreading technique by yourself (e.g., you
may refer to link 4 and 5 for some help).
Q1 (the only question in this task): Write a program that conducts a concurrent preorder traversal
of the BST of task 1 (after executed Q1 ~ Q3), and outputs
1. the result of preorder traversal (i.e., a list of node identities ).
2. the age of a patient whose identity is 6.
About preorder traversal: https://en.wikipedia.org/wiki/Tree_traversal
Hint:
1. You may use a thread pool. In each program run, assign the left subtree to a thread, and assign
the right subtree to a free thread in pool (if any). Otherwise, the thread itself deals with the
searching.
2. An unbalanced binary search tree may make the multi-threading program ineffective because
there will always be one thread dealing with a long subtree while another thread only deals with a
very short tree (see Figure 2), you have to design to make thread assignment fair. (You do not need
to consider the case, however, it’s a plus for making.)
Important
Remember to write a README document that briefly introduce your code in each task and how to
run them (e.g., environment, command). Also, you have to answer some of the questions in your
README.