K-way merge with heaps in Data Structures Theory - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to describe the main data structure used in a k-way merge with heaps.

Data Structures Theory

The primary data structure used in a k-way merge is a [1].

Drag options to blanks, or click blank then click option'

Aqueue

Bstack

Cheap

Dlinked list

Attempts:

3 left

💡 Hint

Common Mistakes

Confusing heap with stack or queue.

Thinking linked list is used for efficient minimum retrieval.

The k-way merge algorithm uses a heap to efficiently find the smallest element among k sorted lists.

2fill in blank

medium

Complete the sentence to explain the initial step in k-way merge using heaps.

Data Structures Theory

Initially, the heap is built by inserting the [1] element from each sorted list.

Drag options to blanks, or click blank then click option'

Alast

Bfirst

Cmiddle

Dlargest

Attempts:

3 left

💡 Hint

Common Mistakes

Choosing last or largest element instead of first.

Assuming middle element is used initially.

The algorithm starts by inserting the first element of each sorted list into the heap to begin merging.

3fill in blank

hard

Fix the error in the explanation of the heap operation during k-way merge.

Data Structures Theory

After extracting the smallest element from the heap, we [1] the next element from the same list into the heap.

Drag options to blanks, or click blank then click option'

Ainsert

Bignore

Cremove

Dswap

Attempts:

3 left

💡 Hint

Common Mistakes

Thinking we remove or ignore the next element instead of inserting it.

Confusing swap with insert operation.

After removing the smallest element, the next element from that list is inserted into the heap to continue the merge.

4fill in blank

hard

Fill both blanks to describe the heap size and complexity in k-way merge.

Data Structures Theory

The heap size is [1] to the number of lists, and each insertion or extraction takes [2] time.

Drag options to blanks, or click blank then click option'

Aequal

Blogarithmic

Clinear

Dconstant

Attempts:

3 left

💡 Hint

Common Mistakes

Assuming heap size grows with total elements instead of number of lists.

Thinking heap operations take linear or constant time.

The heap size equals the number of lists (k), and each heap operation takes logarithmic time relative to k.

5fill in blank

hard

Fill all three blanks to complete the dictionary comprehension representing the k-way merge condition.

Data Structures Theory

merged = [1]: [2] for [3] in range(len(lists)) if lists[[3]]

Drag options to blanks, or click blank then click option'

Ai

Blists[i].pop(0)

Dj

Attempts:

3 left

💡 Hint

Common Mistakes

Using wrong variable names for iteration.

Not checking if the list is non-empty before popping.

This comprehension extracts the first element from each non-empty list indexed by i to merge them.