Welcome to "Generating Software Tests"! Software has bugs, and catching bugs can involve lots of effort. This book addresses this problem by automating software testing, specifically by generating tests automatically. Recent years have seen the development of novel techniques that lead to dramatic improvements in test generation and software testing. They now are mature enough to be assembled in a book – even with executable code.
from fuzzingbook_utils import YouTubeVideo YouTubeVideo("w4u5gCgPlmg")
You can use this book in four ways:
You can read chapters in your browser. Check out the list of chapters in the menu above, or start right away with the introduction to testing or the introduction to fuzzing. All code is available for download.
You can interact with chapters as Jupyter Notebooks (beta). This allows you to edit and extend the code, experimenting live in your browser. Simply select "Resources $\rightarrow$ Edit as Notebook" at the top of each chapter. Try interacting with the introduction to fuzzing.
You can use the code in your own projects. You can download the code as Python programs; simply select "Resources $\rightarrow$ Download Code" for one chapter or "Resources $\rightarrow$ All Code" for all chapters. These code files can be executed, yielding (hopefully) the same results as the notebooks. Even easier: Install the fuzzingbook Python package.
You can present chapters as slides. This allows for presenting the material in lectures. Just select "Resources $\rightarrow$ View slides" at the top of each chapter. Try viewing the slides for the introduction to fuzzing.
This work is designed as a textbook for a course in software testing; as supplementary material in a software testing or software engineering course; and as a resource for software developers. We cover random fuzzing, mutation-based fuzzing, grammar-based test generation, symbolic testing, and much more, illustrating all techniques with code examples that you can try out yourself.
The interactive notebook uses the mybinder.org service, which runs notebooks on their own servers. Starting Jupyter through mybinder.org normally takes about 30 seconds, depending on your Internet connection. If, however, you are the first to invoke binder after a book update, binder recreates its environment, which will take a few minutes. Reload the page occasionally.
As mybinder.org is a research pilot project, the main goal for the project is to understand usage patterns and workloads for future project evolution. While we strive for site reliability and availability, we want our users to understand the intent of this service is research and we offer no guarantees of its performance in mission critical uses.
There are alternatives to mybinder.org; see below.
If mybinder.org does not work or match your needs, you have a number of alternatives:
Download the Python code (using the menu at the top) and edit and run it in your favorite environment. This is easy to do and does not require lots of resources.
Download the Jupyter Notebooks (using the menu at the top) and open them in Jupyter. Here's how to install jupyter notebook on your machine.
Run the notebook locally in a Docker container. For more information, see How to use the book with Docker.
We try to keep the code as general as possible, but occasionally, when we interact with the operating system, we assume a Unix-like environment (because that is what Binder provides). To run these examples on your own Windows machine, you can install a Linux VM or a Docker environment.
Thanks for referring to our work! Once the book is complete, you will be able to cite it in the traditional way. In the meantime, just click on the "cite" button at the bottom of the Web page for each chapter to get a citation entry.
We're always happy to get suggestions! If we missed an important reference, we will of course add it. If you'd like specific material to be covered, the best way is to write a notebook yourself; see our Guide for Authors for instructions on coding and writing. We can then refer to it or even host it.
We have successfully used the material in various courses.
Initially, we used the slides and code and did live coding in lectures to illustrate how a technique works.
Now, the goal of the book is to be completely self-contained; that is, it should work without additional support. Hence, we now give out completed chapters to students in a flipped classroom setting, with the students working on the notebooks at their leisure. We would meet in the classroom to discuss experiences with past notebooks and discuss future notebooks.
We have the students work on exercises from the book or work on larger (fuzzing) projects. We also have students who use the book as a base for their research; indeed, it is very easy to prototype in Python for Python.
Download the Jupyter Notebooks (using the menu at the top) and adapt the notebooks at your leisure (see above), including "Slide Type" settings. Then,
At this point, we do not provide support for PDF versions. We will be producing PDF and print versions after the book is complete.
We prioritize issues as follows:
Again, we're glad you're here! We are happy to accept
See our Guide for Authors for instructions on coding and writing.