Mastery Points
0
Basics of DSA in dsa
Context & Logic
DSA basics involve understanding time and space complexity, recursion, and dry run techniques. These fundamentals help in analyzing and optimizing algorithms.
Example
O(1) < O(log n) < O(n) < O(n log n) < O(n²) < O(2ⁿ)Step-by-Step Logic
1
Simplify the algorithm to its core operations.
2
Identify the dominant term (highest power of n).
3
Consider the worst-case scenario (Big-O).
4
For recursion, define a base case to prevent stack overflow.
5
Iterative approach: Use loops; Recursive approach: Use self-calls with smaller inputs.
Complexity Metrics
Time Efficiency
Varies per algorithm
Memory Footprint
O(1) for iterative, O(n) for recursive stack