Etna: An Evaluation Platform for Property-Based Testing
For researchers and practitioners in functional programming, ETNA provides a much-needed standardized platform for evaluating and comparing PBT tools and strategies.
The paper introduces ETNA, a platform for empirical evaluation and comparison of property-based testing (PBT) techniques, addressing the lack of rigorous comparisons in the field. It demonstrates its utility through experiments with popular PBT frameworks across five languages, enabling clearer understanding of best practices and tradeoffs.
Property-based testing is a mainstay of functional programming, boasting a rich literature, an enthusiastic user community, and an abundance of tools~ -- so many, indeed, that new users may have difficulty choosing. Moreover, any given framework may support a variety of strategies for generating test inputs; even experienced users may wonder which are better in any given situation. Sadly, the PBT literature, though long on creativity, is short on rigorous comparisons to help answer such questions. We present ETNA, a platform for empirical evaluation and comparison of PBT techniques. ETNA incorporates a number of popular PBT frameworks and testing workloads from the literature, and its extensible architecture makes adding new ones easy, while handling the technical drudgery of performance measurement. To illustrate its benefits, we use ETNA to carry out several experiments with popular PBT approaches in Rocq, Haskell, OCaml, Racket, and Rust, allowing users to more clearly understand best practices and tradeoffs.