Analysis of Algorithms
Last Updated :
23 Jul, 2025
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Analysis of Algorithms is a fundamental aspect of computer science that involves evaluating performance of algorithms and programs. Efficiency is measured in terms of time and space.
Basics on Analysis of Algorithms:
- Why is Analysis Important?
- Order of Growth
- Asymptotic Analysis
- Worst, Average and Best Cases of Algorithms
Asymptotic Notations:
- Big-O Notation
- Theta - Θ Notation
- Big – Ω (Big- Omega) Notation
- Time Complexity
- Space Complexity
- Big O vs, Big Omega vs Theta
- Examples of Big-O analysis
- Practice Questions on Time Complexity Analysis
- Quiz on Time Complexity Analysis
Analysis Examples
Some Advance topics:
- P, NP, CoNP, NP hard and NP complete
- Proof that Clique Decision problem is NP-Complete
- Proof that Independent Set in Graph theory is NP Complete
- Prove that a problem consisting of Clique and Independent Set is NP Complete
- Prove that Dense Subgraph is NP Complete by Generalisation
- Prove that Sparse Graph is NP-Complete
Analysis of Algorithms (Background)
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Analysis of Algorithms (Background)
Order of Growth
Big O Notation
Omega Notation
Theta Notation | Video
Analysis of Common Loops
Analysis of Recursion
