Answer:
b. The names in the list should be in alphabetical order.
Explanation:
A binary search is an algorithm used for searching for an item in a list or array. The algorithm first sorts the data structure into order and then divides it into halves. If the searched item is less than the middle item in the list, then the algorithm searches for the target in the first half, else, in the second half. This reduces the time complexity of the search.
Answer:
See in Explanation
Explanation:
All you know is that an 
algorithm is eventually (a lot) faster than an 
algorithm, but for any specific value of n, you can't say anything. Indeed, the asymptotic growth of the function doesn't depend on its value on 
. This means that if 
then for all 
, the following function is also :
So asymptotic notation is completely uninformative regarding the performance of algorithms on specific values of n.
You could say that functions such as 
are artificial and never really occur in practice. This is not quite true (you can hard-code some auxiliary information for small n, for example), but even if you consider "natural" functions, asymptotic notation doesn't help you to determine anything other than asymptotic's: consider for example 
against 
(such examples definitely happen in practice, for example in fast matrix multiplication).
In python the % operator is modulo. Modulo returns the remainder of two numbers.
19 % 5 = 4 therefore,
print(x%y) would output 4
Answer:
Required code is given below:
Explanation:
def add_to_dict(dictt, key,value):
if key in dictt.keys():
print("Error. Key already exists.")
else:
dictt[key]=value
return dictt
def remove_from_dict(dictt,key):
try:
dictt[key]
dictt.pop(key, None)
return dictt
except KeyError:
print("No such key exists in the dictionary.")
def find_key(dictt,key):
try:
value=dictt[key]
print("Value: ", value)
except KeyError:
print("Key not found.")
