Consider the following hash table, and a hash function of key % 10. How many list items will be compared for the search operations?

HashInsert(newTable, item 25)

HashInsert(newTable, item 54)

HashRemove(newTable, 27)

HashInsert(newTable, item 84)

HashInsert(newTable, item 83)

HashSearch(newTable, 72)

HashSearch(newTable, 77)

HashSearch(newTable, 63)

Question

Consider the following hash table, and a hash function of key % 10. How many list items will be compared for the search operations?

HashInsert(newTable, item 25)

HashInsert(newTable, item 54)

HashRemove(newTable, 27)

HashInsert(newTable, item 84)

HashInsert(newTable, item 83)

HashSearch(newTable, 72)

HashSearch(newTable, 77)

HashSearch(newTable, 63)

BlackTom AI · Accepted Answer

The question presents a hash table using a hash function key % 10 and a sequence of operations, then asks how many list items will be compared for the search operations.

First, restate the setup: with chaining, each key is placed into bucket index key % 10. The inserts are:
- Insert 25 -> bucket 5
- Insert 54 -> bucket 4
- Remove 27 -> not present, so nothing changes
- Insert 84 -> bucket 4 (collides with 54)
- Insert 83 -> bucket 3

Now, analyze the searches:
- Search 72: bucket 72 % 10 = 2. Bucket 2 has not been used by any insert, so it is empty. Searching an empty bucket requires 0 list item comparisons because you immediately know the item cannot be present in that bucket.
- Search 77: bucket 77 % 10 = 7. Bucket 7 is also empty (no item has been placed there), so this search also requires 0 list item comparisons.
- Search 63: bucket 63 % 10 = 3. Bucket 3 currently contains 83 (from the insert of 83). To determine if 63 is in the list, you compare 63 with the first node in the bucket, which holds 83. Since it does not match, you conclude the item is not in the bucket after that single comparison. Therefore, this search requires 1 list item comparison.

Summarizing the per-search comparisons: 0 for searching 72, 0 for searching 77, and 1 for searching 63. If the question intends the counts per search in that order, the sequence would be 0; 0; 1. If it intends the total number of comparisons across all three searches, the total would be 1.

Important note: The provided data includes an "answer" value of '2; 0; 1' but the answer options field is empty. Because the options are missing, we cannot map the numeric results to specific labeled choices. The analysis above is based on standard chaining behavior and the given operations. The discrepancy (2; 0; 1) likely indicates either a misprint in the provided answer or an alternative counting convention, but with the usual hashing and chaining interpretation, the counts per search are 0, 0, and 1 respectively, yielding a total of 1 across all three searches.

类似问题

Open Addressing One of the advantages of chained hash table over the open addressing scheme is ______

Open Addressing One of the advantages of chained hash table over the open addressing scheme is ______

What is the worst-case complexity of get in separate chaining? (Make no assumption about the load factor or how good the hash function is.)

What is the worst-case complexity of insert in separate chaining? (Make no assumption about the load factor or how good the hash function is.)

In a separate chaining hashtable, what is the impact of increasing the load factor above 1?

Consider the hash table of size 11 that uses linear probing shown below, where the hash function is h(k) = (k mod 11). Thus h(14)=3, h(25)=3. What indices are examined if we now perform get(4)?

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?

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类似问题

Open Addressing One of the advantages of chained hash table over the open addressing scheme is ______

Open Addressing One of the advantages of chained hash table over the open addressing scheme is ______

What is the worst-case complexity of get in separate chaining? (Make no assumption about the load factor or how good the hash function is.)

What is the worst-case complexity of insert in separate chaining? (Make no assumption about the load factor or how good the hash function is.)

In a separate chaining hashtable, what is the impact of increasing the load factor above 1?

Consider the hash table of size 11 that uses linear probing shown below, where the hash function is h(k) = (k mod 11). Thus h(14)=3, h(25)=3. What indices are examined if we now perform get(4)?

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?

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.