In this class you will learn how to debug programs systematically, how to automate the debugging process and build several automated debugging tools in Python.
Overview
Syllabus
- How Debuggers work
- Theory: Scientific method and its application to debugging.,Fun fact: First bug in the history of computer science.,Practice: Building a simple tracer.
- Asserting Expectations
- Theory: Assertions in testing and in debugging.,Fun fact: The most expensive bug in history.,Practice: Improving the tracer.
- Simplifying Failures
- Theory: Strategy of simplifying failures. Binary search. Delta debugging principle.,Fun fact: Mozilla bugathon.,Practice: Building a delta debugger.
- Tracking Origins
- Theory: Cause-effect chain. Deduction. Dependencies. Slices.,Fun fact: Sherlock Holmes and Doctor Watson.,Practice: Improving the delta debugger.
- Reproducing Failures
- Theory: Types of bugs (Bohr bug, Heisenbug, Mandelbug, Schrodinbug). Systematic reproduction process.,Fun fact: Mad laptop bug.,Practice: Building a statistic debugging tool.
- Learning from Mistakes
- Theory: Bug database management. Classifying bugs. Bug maps. Learning from mistakes.,Fun fact: Programmer with the most buggy code.,Practice: Improving your tools and practicing on a real world bug database.
Taught by
Andreas Zeller
