Which approach is commonly used to merge two sorted singly linked lists into a single sorted list?

Master Linked Lists Structures for Data Structures Tests. Utilize flashcards and multiple choice questions with detailed explanations for each, ensuring your readiness for the exam!

Multiple Choice

Which approach is commonly used to merge two sorted singly linked lists into a single sorted list?

Explanation:
Merging two sorted lists by always choosing the smaller next node preserves the overall order as you build the result. Using a dummy head makes this process clean and robust because you don’t need special handling for the first node—you simply attach nodes to a tail as you go. Here's how it works: create a dummy node and a tail pointer that starts at the dummy. Have pointers to the current nodes of both lists. Compare their values; attach the smaller node to tail.next, and advance that list’s pointer. Move the tail forward. Repeat until one list runs out, then link the remaining non-empty list to tail.next. Finally, return dummy.next as the head of the merged list. This approach is optimal for correctness and efficiency: it maintains sorted order by always picking the smaller current value, handles edge cases smoothly with the dummy head, runs in linear time proportional to the total number of nodes (O(n + m)), and uses constant extra space since it reuses existing nodes. Attaching without comparisons would break order, and reversing lists before concatenation would not yield a sorted result without extra steps.

Merging two sorted lists by always choosing the smaller next node preserves the overall order as you build the result. Using a dummy head makes this process clean and robust because you don’t need special handling for the first node—you simply attach nodes to a tail as you go.

Here's how it works: create a dummy node and a tail pointer that starts at the dummy. Have pointers to the current nodes of both lists. Compare their values; attach the smaller node to tail.next, and advance that list’s pointer. Move the tail forward. Repeat until one list runs out, then link the remaining non-empty list to tail.next. Finally, return dummy.next as the head of the merged list.

This approach is optimal for correctness and efficiency: it maintains sorted order by always picking the smaller current value, handles edge cases smoothly with the dummy head, runs in linear time proportional to the total number of nodes (O(n + m)), and uses constant extra space since it reuses existing nodes. Attaching without comparisons would break order, and reversing lists before concatenation would not yield a sorted result without extra steps.

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