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Linked Lists, Trees, Inheritance ICS-33
创建日期：2024-04-01 17:46:20
所属分类：物理Physical
标签： ICS-33
Linked Lists, Trees, Inheritance
1. (4 pts) Examine the mystery method and hand simulate the call mystery(x); using the linked list below. Lightly
cross out ALL references that are replaced and Write in new references: don’t erase any references. It will look a bit
messy, but be as neat as you can. Show references to None as /. Do your work on scratch paper first.
def mystery(l):
while l.next != None and l.next.next != None:
t1 = l.next
t2 = t1.next
t1.next = t2.next
t2.next = t1
l.next = t2
l = t1

2. (2 pts) Draw the binary search tree that results from inserting the following values (in the following order) into an
empty binary search tree: 13, 10, 6, 5, 8, 3, 4, 16, 11, 17, 1, 2, 15, 19, 18, 14, 9, 20, 7, and 12. Draw the number for
each tree node, with lines down to its children nodes. Space-it-out to be easy to read. Answer the questions in the box.

Size =

Height =
class LN:
def __init__(self, value, next=None):
self.value, self.next = value, next

class TN:
def __init__(self, value, left=None, right=None):
self.value, self.left, self.right = value, left, right

For Problems 1 and 2, print the Answers.pdf file (in the q6helper folder and on Gradescope), write your answers on it, then upload it to
Gradescope by Friday 11/27 at 11:30pm. If you cannot print files, write your answer as best you can on a blank sheet of paper and upload it to
Gradescope. Upload your solutions to problems 3-6 in the q6solution.py file the normal way to Checkmate by Thursday 11/26 at 11:30pm.
Submit Solution on Gradescope
Submit Solution on Gradescope
3. (4 pts) Define an iterative function named separate; it is passed one linked list and a predicate; it returns a
2-tuple of two linked lists: the first is a linked list of all the values in the parameter where the predicate returns
True; the second is a linked list of all the values in the parameter where the predicate returns False; the values
in each list must be the reverse of their order in the parameter linked list (this makes the code easier to write, not
harder: adding a value at the front of a linked list is easier). For example if we defined
a = list_to_ll([1,2,3,4,5,6])
writing even,odd = separate(a,lambda x : x%2 == 0) results in even referring to a linked list
containing the values 6, 4, and 2 (in that order) ; odd referring to a linked list containing the values 5, 3,
and 1 (in that order). You may not use Python lists, tuples, sets, or dicts in your code: just use linked lists.
4. (4 pts) A min-heap is a binary tree whose order property is that every node is strictly smaller than any of
its children (if a left/right child is None, you don’t have to check it). Write the recursive function
is_min_heap which checks this order property for every node in the tree and returns True if the binary
tree is a min-heap and False if it is not. Think symmetry.
5. (4 pts) We learned that when we declare a class using inheritance, the __bases__ attribute of the class is
bound to a tuple of references to its base classes. Write a recursive function named bases that takes a
reference to any class and returns a set containing that class and all its base classes (all the way back to the
object class). You may not use the __mro__ or mro attributes of the class, which would trivialize your
function. You may use both iteration (over the __bases__ list) and recursion to write this function. For
example, given the following class definitions in a script (class A appears as __main__.A)
class F:pass
class C:pass
class G:pass
class B(F):pass
class D(G):pass
class A(B,C,D):pass
Hint: the union method for a set takes any number of arguments (other sets: a.union(b,c,d)) and computes
the union of all of them Remember how to use * to take a tuple of sets and convert them into that many set
arguments in a function call.. You can also use functools.reduce with | (the set union operator: a | b).
6. (7 pts) Define a class named popdict, derived from the dict class; in addition to being a dictionary, it
remembers how often each key is accessed (how popular it is), and iterates through the popdict in
decreasing order of how frequently the key was accessed. Besides storing the standard dictionary of keys and
their values, a popdict stores an auxiliary dictionary remembering how often each key has been accessed.
The keys in the actual dictionary should always be the same as the keys in the auxiliary dictionary. See the
notes for how pdefaultdict is derived from dict; this derivation is similar.
Define the derived class popdict with only the following methods:
• __init__ (self,initial_dict=[],**kargs): initializes the dictionary and also creates an auxiliary
popularity dictionary (I used a defaultdict) for remembering how often each key is accessed: initialize this
popularity dictionary so that it shows each key in the newly initialized dictionary as being used once so far.
• __getitem__ (self,key): for any key in the dictionary, return its associated value and increase its
popularity (how often it has been used) by 1 in the popularity dictionary.
• __setitem__ (self,key,value): set key to associate with value in the dictionary and increase its
popularity (how often it has been used) by 1 in the popularity dictionary.
Calling bases(A) returns the set

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MOEC0021 STA 106 ENGG 1300A ENGG 1300 OLET1139 STAT 3503 STAT 206 FEM11149 ELEN 4720 COMP20003 SOLA1070 CS574 C11CS LINB29H3 MAST90083 ECON7200 STAT 610 LINB29 DSM-5 COMP3161 EEEN40010 MATH 4431 K353 STA 3386 IERG4300 COMS W4167 ENG5298 AMME 2302 CS3910 COMPSCI 320 STATS 369 GR5242 COSC 328 CSCI435 MGTS1301 INFS2200 COMP3900 CIS 375 Module AE03 COMP3121 CS260 HAM503 MGMT5050 INT3075 COSC 285 GEOL0029 GEGE2X01 STAT1201 MATH1061 MMF1941H STAT 5060 CS 520 COMP 4320 MSIN0104 000T FINS3648 ECMT2160 ECON4003 Phys 129L CSE 142 CS 3130 MGEB01 EECS 340 Finance (20443/20444) ECMM149 COMP5310 EEEN60180 CSC 111 AT2 CSCI 4430 STAB57 MA/CSC 427 MATH322 D100 CSCI544 CITS3004 CI6227 CSE 565 APCO 1P01 852L1 ELEC S411F COMP3207 STATS330 ECON7530 FIT5149 CSI4104 CMPT 371 COMP201 SEHS4696 FI4003 MATH6182 CG1 WS MATH401 MGT 205 QTM 110 COMP 0137 MACE12201 FIT5210 ECE 544 BISM7206 HUDM 6055 ECON3203 STATS 210 MSCI 570 MATH6173 COMPSCI4039 Accounting COM3503 AOE2024 ECON213 PSYC10004 Control Data 100/200A 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