Property-based testing (PBT) is a testing methodology where users write executable formal specifications of software components and an automated harness checks these specifications against many automatically generated inputs. From its roots in the QuickCheck library in Haskell, PBT has made significant inroads in mainstream languages and industrial practice at companies such as Amazon, Volvo, and Stripe. As PBT extends its reach, it is important to understand how developers are using it in practice, where they see its strengths and weaknesses, and what innovations are needed to make it more effective.

We address these questions using data from 30 in-depth interviews with experienced users of PBT at Jane Street, a financial technology company making heavy and sophisticated use of PBT. These interviews provide empirical evidence that PBT’s main strengths lie in testing complex code and in increasing confidence beyond what is available through conventional testing methodologies, and, moreover, that most uses fall into a relatively small number of high-leverage idioms. Its main weaknesses, on the other hand, lie in the relative complexity of writing properties and random data generators and in the difficulty of evaluating their effectiveness. From these observations, we identify a number of potentially high-impact areas for future exploration, including performance improvements, differential testing, additional high-leverage testing scenarios, better techniques for generating random input data, test-case reduction, and methods for evaluating the effectiveness of tests.