Search Algorithms
Master the art of finding elements efficiently. From simple linear searches to advanced logarithmic algorithms.
Why Learn Search Algorithms?
Fundamental Skill
Searching is one of the most common operations in programming. Understanding different approaches helps you choose the right tool for each situation.
Performance Optimization
From O(n) to O(log n) - learn how algorithm choice dramatically impacts performance, especially with large datasets.
Real-world Applications
From database queries to web search engines, these algorithms power the technology we use every day.
Algorithm Categories
Basic Algorithms
Simple, intuitive approaches that work on any data structure.
- • Linear Search
- • No prerequisites
- • Easy to understand
Sorted Array Algorithms
Efficient algorithms that require sorted input data.
- • Binary, Jump, Exponential
- • Logarithmic time complexity
- • Divide and conquer
Specialized Algorithms
Advanced techniques for specific data distributions.
- • Fibonacci, Ternary
- • Interpolation Search
- • Mathematical optimizations
Linear Search
BeginnerSequential search through each element until target is found
Binary Search
BeginnerDivide and conquer search that halves the search space each time
Jump Search
IntermediateBlock-based search that jumps ahead by fixed steps
Interpolation Search
IntermediateEstimates position based on value distribution in uniformly distributed data
Exponential Search
IntermediateFinds range by exponential jumps, then performs binary search
Fibonacci Search
AdvancedUses Fibonacci numbers to divide array into optimal sections
Ternary Search
AdvancedDivides array into three parts, eliminating 2/3 of search space
Block Search
IntermediateDivides array into blocks and searches sequentially within blocks
Time Complexity Comparison
| Algorithm | Best Case | Average Case | Worst Case | Space |
|---|---|---|---|---|
| Linear Search | O(1) | O(n) | O(n) | O(1) |
| Binary Search | O(1) | O(log n) | O(log n) | O(1) |
| Jump Search | O(1) | O(√n) | O(√n) | O(1) |
| Interpolation Search | O(1) | O(log log n) | O(n) | O(1) |
| Exponential Search | O(1) | O(log n) | O(log n) | O(1) |
| Fibonacci Search | O(1) | O(log n) | O(log n) | O(1) |
| Ternary Search | O(1) | O(log₃ n) | O(log₃ n) | O(1) |
* Interpolation Search requires uniformly distributed sorted data for optimal performance
Ready to Start Learning?
Begin with Linear Search to understand the basics, then progress to more advanced algorithms.
Start with Linear Search