Having said this, many of the techniques in this book can also be applied to C and other code. Also, Python code allows us (and you) to focus on the main concepts, rather than implementation details that are out of place in a textbook. Instrumenting code, say for dynamic slicing, gets us savings of similar magnitude. Building an interactive debugger in Python is less than 100 lines of code and took us 2-3 days doing the same for C is tens of thousands of lines and a year-long project.

We use Python to implement our tools and techniques because we can get things done quickly. Try viewing the slides for how debuggers work.ĭo your techniques apply to Python programs only? How about C code? ¶ Just select 'Resources → View slides' at the top of each chapter. This allows for presenting the material in lectures. Once the book is out of beta, you can also install the Python package. These code files can be executed, yielding (hopefully) the same results as the notebooks. You can download the code as Python programs simply select 'Resources → Download Code' for one chapter or 'Resources → All Code' for all chapters. You can use the code in your own projects.

Try interacting with the introduction to interactive debuggers. Simply select 'Resources → Edit as Notebook' at the top of each chapter. This allows you to edit and extend the code, experimenting live in your browser. You can interact with chapters as Jupyter Notebooks (beta). Check out the list of chapters in the menu above, or start right away with the introduction to debugging or how debuggers work. A Textbook for Paper, Screen, and KeyboardĪ Textbook for Paper, Screen, and Keyboard ¶.

C debugging questions pdf