jqwik
JQF
Our great sponsors
| jqwik | JQF | |
|---|---|---|
| 7 | 3 | |
| 521 | 626 | |
| 2.3% | - | |
| 9.2 | 6.3 | |
| 5 days ago | 7 months ago | |
| Java | Java | |
| Eclipse Public License 2.0 | BSD 2-clause "Simplified" License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
jqwik
- Jqwik – Property-Based Testing on the JUnit Platform
- Any library you would like to recommend to others as it helps you a lot? For me, mapstruct is one of them. Hopefully I would hear some other nice libraries I never try.
-
Built a library to help generate test pojos with relevant but random data. I’d love some feedback.
See https://jqwik.net
- I just implemented a method that checks if a binary tree is symmetric, and now I want to test it with Junit. Do I need to manually create a bunch of trees, or is there an easier way?
-
Simple example of property-based testing
Once we knew which property to use it was very straightforward to add a property-based test for it. We used the jqwik library. We like it because it has very good documentation and it is integrated with Junit.
-
must known frameworks/libs/tech, every senior java developer must know(?)
Jqwik - I love property based testing and the way it can make you think differently about some of your code.
-
Mutation testing java projects
Different to mutation testing, but on a semi-relatednpath, I've found property-based testing (e.g. https://jqwik.net/) to be valuable - thinking about the “shape“ of the expected output and getting a bunch of pseudorandom tests is pretty handy, especially for utility functions.
JQF
-
CS 6120: Advanced Compilers: The Self-Guided Online Course
We are working on projects related with cybersecurity and compilers. A reference we look at is [1] and [2]. I think we can publish the results in the coming months.
[1] https://github.com/rohanpadhye/jqf/wiki/Fuzzing-a-Compiler
-
GitHub Copilot for JetBrains and Neovim
QuickcCheck-type tools (generators for tests that know about the edge cases of a domain - e. g. for the domain of numbers considering things like 0, the infinities, various almost-and-just-over powers of two, NaN and mantissas for floats, etc.):
* QuickCheck: https://hackage.haskell.org/package/QuickCheck
* Hypothesis: https://hypothesis.readthedocs.io/en/latest/
* JUnit QuickCheck: https://github.com/pholser/junit-quickcheck
Fuzz testing tools (tools which mutate the inputs to a program in order to find interesting / failing states in that program). Generally paired with code coverage:
* American Fuzzy Lop (AFL): https://github.com/google/AFL
* JQF: https://github.com/rohanpadhye/JQF
Mutation / Fault based test tools (review your existing unit coverage and try to introduce changes to your _production_ code that none of your tests catch)
* PITest: https://pitest.org/
-
Jazzer brings modern fuzz testing to the JVM
If you are interested in fuzzing your Java code, you should also have a look at the JQF project which directly integrates with junit tests: https://github.com/rohanpadhye/JQF
What are some alternatives?
junit-quickcheck - Property-based testing, JUnit-style
Deep Dive - Fluent assertions library for Java
fuzzing - Tutorials, examples, discussions, research proposals, and other resources related to fuzzing
Testcontainers - Testcontainers is a Java library that supports JUnit tests, providing lightweight, throwaway instances of common databases, Selenium web browsers, or anything else that can run in a Docker container.
fast-check - Property based testing framework for JavaScript (like QuickCheck) written in TypeScript
webtau - WebTau (web test automation) is a testing API, command line tool and a framework to write unit, integration and end-to-end tests. Test across REST-API, WebSocket, GraphQL, Browser, Database, CLI and Business Logic with a consistent set of matchers and concepts. REPL mode speeds-up tests development. Rich reporting cuts down investigation time.
copilot-docs - Documentation for GitHub Copilot
aws-junit5 - JUnit 5 extensions for AWS
fuzzcheck-rs - Modular, structure-aware, and feedback-driven fuzzing engine for Rust functions
console-captor - 🎯 ConsoleCaptor captures console output for unit and integration testing purposes
copilot.vim - Neovim plugin for GitHub Copilot