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CS 301 算法分析

【CS 301 算法分析】CS 301
Basic Algorithms (CS 301, Section 1), Professor Yap – Fall 2021
HOMEWORK
October 12, 2021
Homework 4 Due: Tuesday Oct 19, 2021
INSTRUCTIONS:
? Carefully read the Class Integrity Policy in our Class Wiki.
? Go to our Homework Page for general information about Homework.
? REMEMBER: all answers must show some justification! This is even true when the
actual answer is short. E.g., in True/False questions or questions that ask for a single
number for an answer.
QUESTIONS:
Q 1. (5+10+5+10+10 Points) Priority Queues
Refer to Lecture 4 (4-pqueues.pdf) for this question. A priority queue is an ADT
(abstract data type) supporting two operations: insert(key) and deleteMin(). This
can be implemented using a binary heap data structure. The binary heap is a binary
tree of a special shape, that is represented by an array A[1...N]. If the current size
of the queue is n then we have 0 ≤ n ≤ N. Thus the variable n is part of the data
representation, and it is incremented (resp., decremented) after an insert(k) (resp.,
a deleteMin()).
(a) Please do a hand-simulation to insert the key 0 (zero) into the Binary Heap of
Figure 1. Imitate Slide 2 of Lecture 4 in its hand-simulation of insert(2). The
idea is to let the key 2 “float up” as much as possible.
Figure 1: insert(0) into this Binary Heap
HINT: Please display the arrays A[1..n] as a binary tree, not a sequence of keys!
Why? Because we humans are incredibly good with visual images; leave the sequences
to computers!
1
(b) Give the pseudo-code for insert(k) to insert key k into a binary heap. HINT:
Use the macros LeftChild(i), RightChild(i), parent(i) in Slide 4 of Lecture
4 to go up and down the binary tree from any node A[i]!
(c) In some applications, we need to maintain several priority queues, and support an
additional operation: merge(P, Q) where P,Q are two priority queues. After this
merge, the queue Q is destroyed, and P contains the merged queue. In Slide 9, it is
stated that merge(P, Q) takes time O(n) where n is size(P)+size(Q). Explain
why this is true. For instance, why isn’t it O(n log n)?
(d) Suppose we begin with the array A[1..10] whose entries are the 10 digits
1, 7, 3, 2, 0, 5, 0, 8, 0, 7. (1)
[Of course, they come from √
3.] Note that binary heaps can have duplicate keys.
Do a hand simulation to convert this array into a binary heap. You MUST use
the O(n) algorithm of Slide 5.
HINT: To show the intermediate work, it is sufficient to show what the binary
tree looks like after processing an entire level.
(e) Slide 10 of Lecture 4 gives an outline of how to implementing priority queues using
a 2-3 tree.
PLEASE MAKE SURE THAT YOU FULLY UNDERSTAND THE OUTLINE!
Give the pseudo-code for computing merge(P,Q) under the 2-3 tree representation.
What is the time complexity?
Q 2. (4+4+4 Points) Split Simulation for 2-3 Tree
Consider the 2-3 tree in Figure 2 (we only show keys in leaves, guides are implicit).
Please perform the split operation at the key 8, resulting in two 2-3 trees: one tree
Figure 2: A 2-3 tree of size 16
has all the keys ≤ 8 and the other has all the keys > 8.
(a) Draw the intermediate result of split(8), which is an ordered list of 2-3 trees
before merging.
(b) Indicate how in what order these trees must be merged in pairs.
(c) Draw the final two trees that result from these merges.
Q 3. (20 Points) Recursive Rank Method for Java class Tree23
In hw2 we gave a pseudo-code for compute the rank function rank(T, x) where T is an
2-3 tree where each internal node is augmented with a count variable. In this question,
we revisit this problem but in a Java-specific setting (no longer pseudo-code). Assume
the Java class Tree23 as in hw3, but augmented with the count variable. Please write
a Java method for the Tree23 class with this header
2
int rank(String x);
Moreover, your algorithm must be recursive and has the correct Java syntax.
HINT: make rank(x) call a recursive method which you may also call rank(...)
(using overloading). If I insert your code into my class Tree23, it should work perfectly
(why not test it yourself?).
Q 4. (30 Points) Recursive Insertion Method for Java class Tree23
Give the pseudo-code for a recursive insertion algorithm for our class Tree23. For
recursion, we use the standard trick trick of writing two (overloaded) insert methods
with these headers:
boolean insert(Item x);
//return true iff insertion succeeded
int insert(Item x, InternalNode u, int h);
//return c in [0..4] where c=0 means failed;
//else c is the new degree of u.
//You must use recursion here.
HINT: We REALLY prefer pseudo-code over Java code! Why? Because pseudocode
is better for “human consumption” and able to accomodate some ambiguity
that humans can overcome. Computer are (will never) be smart enough for this.
Nevertheless, you need enough specificity (e.g., referring to class members, etc) so that
any one familiar with Tree23 can implement it correctly. The order of assignments,
loop structure, etc, may be important details to provide.
To help you along, we provide you with the pseudo-code for the first insert method.

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