Property-Based Testing (PBT) is a widely adopted random testing methodology that combines user-defined logical propositions with automated test case generation.
Over the past two decades, PBT has gained significant traction; today, virtually all major programming languages host multiple competing PBT frameworks, each innovating in interface design and underlying techniques.
As a result of this proliferation, the PBT landscape of today is significantly fragmented. Advances in frameworks have failed to translate to others; tips, tricks, techniques have not been quantitatively evaluated, historical artifacts have led to stalled progress, and our understanding of PBT hasn't shifted to the point it is possible to do so.
This thesis is a step towards consolidation of the PBT knowledge. It combines a conceptual framework for expressing property runners in the wild, a flexible property language, for expressing a variety of property runners distributed throughout the PBT ecosystem; ETNA, the first large-scale evaluation and benchmarking platform for PBT; and DIRT, to address the remaining challenges and mark the future work required for further consolidation.
Alperen is a PhD student at the PLUM lab, working with Leonidas Lampropoulos on Property-Based Testing. He is interested in understanding the implementations of random testing techniques in different languages, domains, and scenarios; and using this understanding to improve the tools and the ecosystems they live in.