Beginner Topic 13 of 52 Data Structures
Open Addressing
Collision strategy probing other slots in the table itself.
How it works
In open addressing every entry lives directly in the table array, and a collision is resolved by probing for another empty slot using a deterministic sequence such as linear probing, quadratic probing or double hashing. Lookup follows the same probe sequence until it finds the key or an empty slot. It has excellent cache behavior and no per-node allocation, but performance drops sharply as the table fills.
Where it is used
Python dictionaries, many high-performance hash maps and embedded systems with tight memory use open addressing. Linear probing is especially fast for small keys.
Common pitfall
Deletion cannot simply empty a slot, because that breaks probe chains; use tombstone markers. Primary clustering slows linear probing, and the table must resize well before it is full, typically at about 70 percent load.
Where it fits in the course
Open Addressing is topic 13 of 52 in Data Structures, rated Beginner. It follows Chaining. The next topic is Trees.
Practice and explore
- Open the interactive lesson, with a mini quiz.
- Take the Data Structures quiz.
- Explore the Hash Table visualizer: Hash function, buckets and chaining collisions.
How to study this topic
- Read the explanation above and restate the definition in your own words.
- Open the interactive lesson and answer its mini quiz.
- Read the common pitfall, then write a short example that avoids it.
- Check your understanding in the Data Structures quiz, and revisit the topic if you miss a question.
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Related topics
- Chaining (Data Structures)
- Trees (Data Structures)
- Hash Collisions (Data Structures)
- Binary Trees (Data Structures)
- Open Data and Licensing (Emerging & Frontier Topics)
- Addressing Modes (Computer Architecture & Logic)
- Open Source Practices (Software Engineering)