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- analysis of algorithms:
- A way to compare algorithms in terms of their run time and/or space requirements.
- machine model:
- A simplified representation of a computer used to describe algorithms.
- worst case:
- The input that makes a given algorithm run slowest (or require the most space).
- leading term:
- In a polynomial, the term with the highest exponent.
- crossover point:
- The problem size where two algorithms require the same run time or space.
- order of growth:
- A set of functions that all grow in a way considered equivalent for purposes of analysis of algorithms. For example, all functions that grow linearly belong to the same order of growth.
- Big-Oh notation:
- Notation for representing an order of growth; for example, \( O(n) \) represents the set of functions that grow linearly.
- An algorithm whose run time is proportional to problem size, at least for large problem sizes.
- An algorithm whose run time is proportional to \( n^2 \), where \( n \) is a measure of problem size.
- The problem of locating an element of a collection (like a list or dictionary) or determining that it is not present.
- A data structure that represents a collection of key-value pairs and performs search in constant time.