Divide and Conquer
Learn about divide and conquer algorithms, with a focus on binary search and binary search trees.
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Key Concepts
Review core concepts you need to learn to master this subject
Divide and Conquer Algorithms
Complexity of Binary Search
Iterative Binary Search
Base case in a binary search using recursion
Updating pointers in a recursive binary search
Binary Search Sorted Dataset
Operation of a Binary Search
Binary Search Performance
Divide and Conquer Algorithms
Divide and Conquer Algorithms
- Divide-and-conquer solves a large problem by recursively breaking it down into smaller subproblems until they can be solved directly.
- Divide-and-conquer works in three steps: divide, conquer, and combine.
- It is more efficient than brute force approaches.
- It is prone to stack overflow error due to the use of recursion.
Binary Search: Conceptual
Lesson 1 of 3
- 1With a sorted data-set, we can take advantage of the ordering to perform a search which is more efficient than going element by element. Let’s say you were looking up the word “Telescope” in the d…
- 2Play with this interactive visualization demonstrating binary search. Refresh the page to play again with a different list.
- 3How efficient is binary search? In each iteration, we are cutting the list in half. The time complexity is O(log N). A sorted list of 64 elements will take at most log 2 (64) = 6 compari…
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