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)

Question

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)

BlackTom AI · Accepted Answer

The question asks about the expected run time complexity of an open addressing hash table when the number of probes exceeds 1, with notation: number of probes = k and table size = n.
Option by option analysis:
- Option "k": While the time to resolve a single lookup/insert in open addressing grows with how many probes you must perform, the standard way to express the overall expected complexity for a hash table operation is in terms of the table size n (and load factor), not directly in terms of k. Saying O(k) would be precise if you are analyzing a single operation in isolation as a function of the number of probes, but the question’s framing emphasizes the typical overall expected complexity as a function of the table size, given that k can vary up to n. Therefore, labeling the complexity as O(k) does not align with the expected-parameter convention used here.
- Option "n": This choice reflects the idea that as probing increases with a nontrivial number of probes, you may end up inspecting a sizable portion of the table. In many analyses of open addressing under nontrivial probe counts, the expected cost grows with the table size, approaching linear in n in the worst or near-worst scenarios. Thus, O(n) is a reasonable and commonly cited expression for the expected time when probes are not bounded by a small constant and the load factor is substantial.
- Option "1": This would imply constant-time performance regardless of probes, which contradicts the open addressing behavior where additional probes directly contribute to more work. Hence it is incorrect for nontrivial probe counts.
- Option "n2": Interpreting as O(n^2) would imply a quadratic time growth with table size, which is not consistent with standard open addressing analyses where the cost grows roughly linearly with table size in typical high-probe scenarios, not quadratically.

In summary, since the question frames the expected complexity in terms of the table size n under nontrivial probing, option "n" is the most fitting choice among the given options. The other options either misrepresent how probe count translates to overall cost (k), or state an implausible constant (1), or exaggerate to a quadratic growth (n2).

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)

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.

Which is TRUE?

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.

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

考试浏览器助手

风格化写作助手

论文查重助手

文献引用助手

课堂转译助手

课堂笔记助手

Quiz搜索助手

学校历年真题

智能刷题助手

智能匹配练习

希望你的学习变得更简单