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Chapter
Understanding the limits of computation is crucial. This chapter gently introduces the concepts of time and space complexity, Big O notation, and the fundamental differences between solvable and computationally intractable problems.
What is Complexity Theory and Why Should We Care?
Measuring the 'Hardness': Time and Space Complexity
Big O Notation: A Common Language for Efficiency
The Algorithm's Playground: Common Complexity Classes
Beyond the 'Easy' Problems: Introducing NP-Completeness
The P vs. NP Question: A Million Dollar Mystery
Navigating the Maze: Strategies for Dealing with Hard Problems