Papers › Pynguin: Automated Unit Test Generation for Python
Pynguin: Automated Unit Test Generation for Python
Stephan Lukasczyk, Gordon Fraser
The archive published only this paper's code-link row. Authors, date and abstract are from arXiv's metadata (CC0), read from the Kaggle arXiv metadata snapshot of 2026-09-12 where its title matched the archive's; the title is the archive's.
Automated unit test generation is a well-known methodology aiming to reduce the developers' effort of writing tests manually. Prior research focused mainly on statically typed programming languages like Java. In practice, however, dynamically typed languages have received a huge gain in popularity over the last decade. This introduces the need for tools and research on test generation for these languages, too. We introduce Pynguin, an extendable test-generation framework for Python, which generates regression tests with high code coverage. Pynguin is designed to be easily usable by practitioners; it is also extensible to allow researchers to adapt it for their needs and to enable future research. We provide a demo of Pynguin at https://youtu.be/UiGrG25Vts0; further information, documentation, the tool, and its source code are available at https://www.pynguin.eu.
Code
Repository list and official/mentioned flags are the archive's, frozen 2025-07-28. Reachability, where shown, is from one Syntology probe window (2026-09-16 to 2026-09-18); repositories not probed show nothing. GitHub stars are not tracked.
Code Syntology ran Syntology
Not run by Syntology. Nothing on this page verifies that the listed code works.
Results from the paper archive 2025-07-28
No leaderboard rows for this paper in the archive.
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections