Running Time Analysis

Characterize Performance with Analysis

Exploration

• Read chapter 5 of A First Course on Data Structures in Python
• Experimentally evaluate performance of algorithms, data structures, and systems in the ds2 package of donsheehy/datastructures
• Note that next week we will cover a new chapter of the book!

Activities

• Monday and Wednesday: Analytical Evaluation
  • Further understand why program performance is critically important
  • Characterize performance patterns in Python programs
  • Use asymptotic analysis to characterize performance
  • Examine Python source code segments to illustrate key points
• Thursday: Start new algorithm engineering project
• Friday: Review complexity class diagrams

Project

Goal

To build and use a Python program, called filesorter, that runs benchmarks to study the performance of sorting different types of data stored in a CSV file.

Steps

• Use File Sorting as your template repository
• Use as your template repository
• Install the project’s dependencies using devenv
• Follow the instructions to complete the project:
  • Week 1: Implement all of the modules in filesorter
  • Week 2: Design and conduct experiments and document experimental results
• Schedule office hours if you have questions

Slides

Full Screen: Week Six: Running Time Analysis through Theoretical Evaluation