Load factor and rehashing in Data Structures Theory - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the sentence to define load factor in hash tables.

Data Structures Theory

Load factor is defined as the ratio of [1] to the number of buckets in a hash table.

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Abucket size

Bnumber of collisions

Cnumber of elements stored

Dhash function complexity

Attempts:

3 left

💡 Hint

Common Mistakes

Confusing load factor with number of collisions.

Using bucket size instead of number of elements.

The load factor measures how full the hash table is by dividing the number of stored elements by the number of buckets.

2fill in blank

medium

Complete the sentence to explain when rehashing is typically triggered.

Data Structures Theory

Rehashing is usually triggered when the load factor exceeds [1] to maintain efficient operations.

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A2.0

B1.0

C0.5

D0.75

Attempts:

3 left

💡 Hint

Common Mistakes

Choosing 1.0 or higher, which is less common.

Selecting a very low value like 0.5 which is too strict.

Rehashing often happens when the load factor goes beyond 0.75 to keep the hash table efficient and reduce collisions.

3fill in blank

hard

Fix the error in the explanation of rehashing.

Data Structures Theory

Rehashing means [1] the hash table size and recalculating the positions of existing elements.

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Aincreasing

Breducing

Ckeeping

Dignoring

Attempts:

3 left

💡 Hint

Common Mistakes

Thinking rehashing reduces the table size.

Assuming rehashing keeps the size the same.

Rehashing involves increasing the hash table size to reduce collisions and redistribute elements.

4fill in blank

hard

Fill both blanks to describe the effect of rehashing on load factor and performance.

Data Structures Theory

After rehashing, the load factor becomes [1] and the average lookup time [2].

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Alower

Bhigher

Cdecreases

Dincreases

Attempts:

3 left

💡 Hint

Common Mistakes

Assuming load factor increases after rehashing.

Thinking lookup time increases after rehashing.

Rehashing lowers the load factor by increasing table size, which decreases average lookup time by reducing collisions.

5fill in blank

hard

Fill all three blanks to complete the explanation of rehashing steps.

Data Structures Theory

Rehashing involves creating a new table with [1] buckets, then [2] each element from the old table, and finally [3] them into the new table.

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Adouble the size

Bremoving

Cinserting

Dhalving the size

Attempts:

3 left

💡 Hint

Common Mistakes

Thinking the new table is smaller.

Confusing removing with inserting steps.

Rehashing creates a new larger table (often double size), removes each element from the old table, and inserts them into the new table to redistribute keys.