Transform linked list to hash map
Last updated: February 11, 2026
Quick Overview
Given a linked list, transform it into a hash map where each unique value from the linked list is a key, and its corresponding value is the count of occurrences of that key in the list. The output should be a hash map with keys representing the unique elements and values representing their frequencies.
ServiceNow
February 11, 2026132
12
4,250 solved
Given a linked list, transform it into a hash map where each unique value from the linked list is a key, and its corresponding value is the count of occurrences of that key in the list. The output should be a hash map with keys representing the unique elements and values representing their frequencies.
This coding problem is frequently asked during Phone Screen at ServiceNow. The interviewer is testing your ability to translate a problem into clean, working code while discussing time and space complexity. ServiceNow expects candidates to write production-quality code, not just solve the puzzle.
What the Interviewer Expects
- Quickly identify the optimal approach and its theoretical basis
- Handle complex algorithm design with multiple interacting components
- Write concise, elegant code under time pressure
- Prove correctness of your approach and discuss alternative solutions
- Optimize beyond the obvious: discuss constant factor improvements
- Address follow-up variations and explain how the solution generalizes
Key Topics to Cover
How to Approach This
- Clarify input constraints and edge cases before writing code.
- Walk through your approach verbally and confirm with the interviewer before coding.
- Start with a brute force solution, then optimize. Mention time and space complexity.
- Test your solution with examples, including edge cases like empty input or duplicates.
- Consider common patterns: sliding window, two pointers, hash map, BFS/DFS, dynamic programming.
Possible Follow-up Questions
- What happens if the input contains duplicates?
- Can you solve this iteratively instead of recursively (or vice versa)?
- What if the input doesn't fit in memory?
- Can you optimize the space complexity of your solution?
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Problem Analysis
The problem requires transforming a linked list into a hash map (dictionary) that counts the occurrences of each unique value. This is a classic use case for a hash map, as it allows for O(1) average ...
Approach
- Initialize an empty hash map (dictionary) to store the frequency of each unique value.
- Start at the head of the linked list.
- For each node, check if its value exists in the hash map:
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