In the process of constructing a Huffman tree, how are two nodes with the lowest frequencies combined? They are merged into a new node with a frequency equal to the sum of their frequencies. They are discarded after updating the frequency count. They are linked as siblings in the tree. They are stored separately for future processing.

They are merged into a new node with a frequency equal to the sum of their frequencies.

What is the primary goal of Huffman tree construction? To maximize the depth of the tree To minimize the average code length To ensure all symbols have the same frequency To convert all symbols into binary strings of equal length

To minimize the average code length

How is a symbol's code determined in a Huffman tree? By the order of insertion into the tree By traversing the tree from the root to the leaf By assigning a random binary string By using a hash function

By traversing the tree from the root to the leaf

What happens if two symbols have the same frequency in Huffman tree construction? The symbols are combined into one node. The order of insertion determines which node is processed first. They cannot be included in the same tree. A tie-breaking rule based on ASCII value is used.

The order of insertion determines which node is processed first.

What is a common misconception about the Huffman coding method? It always results in a balanced tree. It can encode any type of data. It is optimal for all types of data compression. It is a lossy compression technique.

It always results in a balanced tree.

What is the first step in constructing a Huffman tree? List all symbols with their frequencies Sort symbols alphabetically Assign binary codes to symbols Merge all symbols into one

List all symbols with their frequencies

What happens to the two nodes with the smallest frequencies during Huffman tree construction? They are merged into a new node They are discarded They are swapped They are left unchanged

They are merged into a new node

What should you do after creating a new node from two merged nodes? Insert the new node back into the priority queue Remove the new node from the process Assign a binary code to the new node Ignore the new node

Insert the new node back into the priority queue

How does the Huffman tree construction process end? When there is only one node left in the priority queue When all nodes have equal frequency When every node has a binary code When all nodes are merged into pairs

When there is only one node left in the priority queue

What is a key feature of the final Huffman tree? It has a unique prefix code for each symbol All symbols have the same frequency It is a binary search tree All nodes are leaves

It has a unique prefix code for each symbol

What is the main advantage of using Huffman coding? It reduces the average length of codes It increases the average length of codes It simplifies data compression It uses more memory

It reduces the average length of codes

What is the first step in constructing a Huffman tree? Create a list of symbols with their frequencies Build the tree from the leaves Merge the highest frequency nodes Traverse the tree to assign codes

Create a list of symbols with their frequencies

What do you do after creating the list of symbols with frequencies in Huffman tree construction? Sort the list by frequency Insert symbols into a priority queue Assign codes to symbols Merge all symbols into a single node

Insert symbols into a priority queue

How are nodes chosen to be merged in the priority queue during Huffman tree construction? By choosing nodes with the highest frequency Randomly By choosing nodes with the lowest frequency By choosing nodes with equal frequency

By choosing nodes with the lowest frequency

What happens to the frequencies of merged nodes in a Huffman tree? They are summed and assigned to the new node They are divided equally They remain the same They are multiplied

They are summed and assigned to the new node

How do you handle ties in frequencies when merging nodes in a Huffman tree? Merge any two nodes arbitrarily Choose the nodes in alphabetical order Always merge the first two nodes Choose based on external criteria

Merge any two nodes arbitrarily

How does the load factor affect hash table performance? Higher load factor decreases performance Higher load factor increases performance Load factor has no effect Load factor affects only space complexity

Higher load factor decreases performance

What is meant by 'load factor' in the context of hash tables? Ratio of stored elements to table size Average number of collisions Speed of hash computation Amount of memory used

Ratio of stored elements to table size

How does a hash table's load factor influence its performance? Higher load factor improves time complexity Lower load factor increases memory usage Load factor has no impact on performance Higher load factor increases collision probability

Higher load factor increases collision probability

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