Question

•Implement an open addressing hash table to store a list of integers. Your task is to handle collisions using open addressing and implement basic operations such as insertion, deletion, and searching. The open addressing technique you will use is linear probing.

A)Use open addressing

B) Implement an open addressing hash table to store integers

C) Implement this in Python

D) Use linear Probing

E) Use double hashing

Answer 1

An open addressing hash table with linear probing is a data structure in Python for handling integers. It uses an array and a hash function to resolve collisions by searching for the next available slot sequentially.

Step-by-step explanation:

An open addressing hash table is a data structure used to implement an associative array that uses a hash function to compute an index into an array of slots, from which the desired value can be found. In Python, we can implement such a structure to handle integers using linear probing as a collision resolution method. Despite asking for double hashing, we'll ignore that part as per the instruction.

Here's a basic implementation of an open addressing hash table using linear probing in Python:

class LinearProbingHashTable:
def __init__(self, capacity=10):
self.table = [None] * capacity
self.capacity = capacity
self.size = 0

def hash(self, key):
return key % self.capacity

def rehash(self, old_hash):
return (old_hash + 1) % self.capacity

def insert(self, key):
if self.size == self.capacity:
return False
hash_value = self.hash(key)
while self.table[hash_value] is not None:
hash_value = self.rehash(hash_value)
self.table[hash_value] = key
self.size += 1
return True

def search(self, key):
start_slot = self.hash(key)
position = start_slot
while self.table[position] is not None:
if self.table[position] == key:
return True
position = self.rehash(position)
if position == start_slot:
return False
return False

def delete(self, key):
position = self.hash(key)
while self.table[position] is not None:
if self.table[position] == key:
self.table[position] = None
self.size -= 1
return True
position = self.rehash(position)
return False

The class LinearProbingHashTable includes methods for insertion (insert), deletion (delete), and searching (search). When a collision occurs during insertion, the hash table uses linear probing by incrementally searching for the next available slot.

Answer 2

Below is an example of a simple implementation of an open addressing hash table using linear probing in Python to store a list of integers. \

python

class OpenAddressingHashTable:

def __init__(self, size):

self.size = size

self.table = [None] * size

def hash_function(self, key):

return key % self.size

def linear_probe(self, index, attempt):

return (index + attempt) % self.size

def insert(self, key):

index = self.hash_function(key)

attempt = 0

while self.table[index] is not None:

attempt += 1

index = self.linear_probe(index, attempt)

self.table[index] = key

def search(self, key):

index = self.hash_function(key)

attempt = 0

while self.table[index] is not None:

if self.table[index] == key:

return index

attempt += 1

index = self.linear_probe(index, attempt)

return None

def delete(self, key):

index = self.search(key)

if index is not None:

self.table[index] = None

print(f"Key {key} deleted.")

else:

print(f"Key {key} not found.")

can customize the size of the hash table (size parameter) and the hash function based on your requirements.