Intermediate Topic 25 of 52 Data Structures
Segment Trees
Trees answering range queries and updates in logarithmic time.
How it works
A segment tree stores aggregates such as sum, minimum, maximum or gcd for ranges of an array, with each node covering an interval and its children covering the two halves. A range query combines O(log n) nodes, and a point update changes one leaf and its ancestors, also in O(log n). Lazy propagation extends this to range updates without touching every element.
Where it is used
Range sum and range minimum queries with updates, computational geometry, competitive-programming problems, statistics over sliding intervals and finding the number of inversions use segment trees.
Common pitfall
The tree needs about 4n array space and subtle index handling, which causes off-by-one errors. Choosing a combine function that is not associative gives wrong answers. Lazy propagation must push pending updates down before descending. For simple prefix sums, a Fenwick tree is smaller and simpler.
Where it fits in the course
Segment Trees is topic 25 of 52 in Data Structures, rated Intermediate. It follows Tries. The next topic is Fenwick Trees.
Practice and explore
- Open the interactive lesson, with a mini quiz.
- Take the Data Structures quiz.
- Explore the Binary Search Tree visualizer: Insert keys and run traversals.
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
- Tries (Data Structures)
- Fenwick Trees (Data Structures)
- Binary Heap Operations (Data Structures)
- Graphs (Data Structures)
- Decision Trees (AI & Machine Learning)
- Trees in Graph Theory (Theory & Discrete Math)
- Abstract Syntax Trees (Languages & Compilers)