Hash Map: Collision Handling
Software Engineer path · lesson 6 of 99Visualize how internal Hash Tables work! See how keys are hashed to indices and how collisions are resolved using Chaining (Linked Lists).
Syntax: put word n · get word · remove word. Numbers from -99 to 99.
Fewer buckets, longer chains: watch key comparisons.
5 empty buckets. A key's bucket is the sum of its character codes mod 5.
- 1h = (sum of character codes of key) % m
- 2put(k, v): scan bucket h; update k if found, else append (k, v)
- 3get(k): scan bucket h for k
- 4remove(k): scan bucket h; unlink k if found
- 5load factor α = entries / m — long chains mean slow lookups
- Hashes
- 0 / 7
- Key comparisons
- 0 / 4
Tap any element in the diagram to inspect its state at this step.
Keys: ← → step, Space play/pause. Predict mode pauses before key steps and asks what happens next.
put(key, value) with chaining
Order what a chained hash map does on insert.
Tap a piece, then tap where it goes — or drag it. Tap the tray to take one back.
- 1Drop a step here
- 2Drop a step here
- 3Drop a step here
- 4Drop a step here
- 5Drop a step here
Test your knowledge
What is the worst-case time complexity of searching in a Hash Map with Chaining?
Write the code
Two Sum
function twoSum(nums, target) {
// Your code here
}The short version
Think of a library where every book has a specific shelf determined by a formula based on its title. You don't browse; you calculate the exact location and go straight there.
In more depth
Constant Time Magic
A Hash Map (or Hash Table) allows for O(1) average time complexity for Insert, Delete, and Lookup. It works by using a Hash Function to map a key (like a string) to an index in an array.
Collisions:
When two keys map to the same index.
Hash Maps are the single most useful data structure in interviews for trading space for time.
When to reach for this
- Count frequency of elements
- Check existence in O(1)
- Map a key to a value (Caching)
Interview Questions
References & Further Reading
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