teach:fpro:lectures:16

**Master in Informatics and Computing Engineering
Programming Fundamentals
Instance: 2018/2019**

—

By the end of this class, the student should be able to:

- Describe why algorithm analysis is important
- Use “Big-O” to describe execution time
- Describe the “Big-O” execution time of common operations on Python lists and dictionaries

- What is Algorithm analysis.
- Order of growth.
- Big-O notation.

- Performance of Python data structures
- Lists
- Dictionaries.

- J. Correia Lopes,
*Script and illustrations*, 16-analysis.pdf - FPRO, 2018/19,
*Python code*, Lecture's on GitHub - Brad Miller and David Ranum, Problem Solving with Algorithms and Data Structures using Python (Section 5.3, Section 5.4) HTML
- Brad Miller and David Ranum, Problem Solving with Algorithms and Data Structures using Python (Chapter 2) HTML

- What is Algorithm analysis. Order of growth. Big-O notation. Performance of Python data structures: Lists, Dictionaries.

— *FPRO, 2018/19*

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teach/fpro/lectures/16.txt · Last modified: 21/11/2018 23:03 by Correia Lopes