Which is TRUE?

Question

Which is TRUE?

BlackTom AI · Accepted Answer

When evaluating the statements, I’ll compare the typical performance characteristics of dictionaries (hash maps) vs. unsorted array-lists.
Option a: 'The performance of the hash function will not affect the runtime of the main dictionary operations.' In practice, the hash function’s quality can affect collision rates, which in turn can impact constant factors and sometimes average-case performance. This statement is misleading because it downplays the role of hashing efficiency and collision handling in runtime.
Option b: 'In practice, it is quicker to update an element in an unsorted array-list than a dictionary.' Updating in an unsorted array-list may require locating the element first, which is O(n) for search, then updating, whereas a dictionary provides direct access to a key via hashing, typically O(1) on average. This makes updates faster on a dictionary, so this claim is generally incorrect.
Option c: 'In practice, it is quicker to search for an element in a dictionary than an unsorted array-list.' This aligns with the standard analysis: a dictionary uses a hash table to map keys to values, giving expected constant time search, while an unsorted array-list requires scanning elements one by one, giving O(n) search. Therefore, this statement is true in typical scenarios.
Option d: 'In practice, it is quicker to delete an element from an unsorted array-list than a dictionary.' Deleting from an unsorted array-list requires locating the element (O(n)) and then removing, whereas a dictionary can typically delete in O(1) time for a given key, assuming hash operations are efficient. This makes the statement generally false.
Thus, after weighing the options, Option c reflects the correct performance comparison between dictionaries and unsorted array-lists in terms of search operations, while the other statements misrepresent or oversimplify the runtime implications of hashing, updates, and deletions.

Which is TRUE?

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Consider an implementation of a hash table with linear probing where the hash function runs in constant time and the cost of comparison is also constant. What is the best-case time complexity of the getitem method? Consider n is the number of items in the hash table.

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Which is TRUE?

查看解析

登录即可查看完整答案

类似问题

Consider an implementation of a hash table with linear probing where the hash function runs in constant time and the cost of comparison is also constant. What is the best-case time complexity of the __getitem__ method? Consider n is the number of items in the hash table.

What is the best case time complexity of deleting a key from a linear probe table?

Question at position 2 About how many steps would be needed when searching for a particular key in a hash map with 1000 nodes?1000150010

HT_Rev_6 A key 48 is to be inserted into a hash table using the hash function h(k)=k mod 10, open addressing, and linear probing for collision handling. Given the current state of the hash table below, where will key 48 be stored?​ ​

HTables_3 Double hashing is a form of open addressing.

HTables_8 During open addressing, if the number of probes exceeds 1, expected run time complexity of the hash table becomes O(____). (number of probes = k, size of table =n)

HMap_1 In the implementation discussed in our lectures, Hash Tables using Linear Probing to resolve collisions increase the likelihood of finding an empty slot if the load factor is less than or equal to:

更多留学生实用工具

希望你的学习变得更简单

Consider an implementation of a hash table with linear probing where the hash function runs in constant time and the cost of comparison is also constant. What is the best-case time complexity of the getitem method? Consider n is the number of items in the hash table.

HT_Rev_6 A key 48 is to be inserted into a hash table using the hash function h(k)=k mod 10, open addressing, and linear probing for collision handling. Given the current state of the hash table below, where will key 48 be stored?