Trace-Guided Synthesis of Effectful Test Generators
This work addresses the challenge of testing effectful systems for developers and testers, offering an incremental improvement by adapting existing underapproximate program logic ideas to type systems.
The paper tackles the problem of generating effective test sequences for effectful black-box systems by integrating underapproximate reasoning into a type and effect system, resulting in synthesized test generators that are significantly more effective than default strategies and competitive with state-of-the-art handwritten solutions.
Several recently proposed program logics have incorporated notions of underapproximation into their design, enabling them to reason about reachability rather than safety. In this paper, we explore how similar ideas can be integrated into an expressive type and effect system. We use the resulting underapproximate type specifications to guide the synthesis of test generators that probe the behavior of effectful black-box systems. A key novelty of our type language is its ability to capture underapproximate behaviors of effectful operations using symbolic traces that expose latent data and control dependencies, constraints that must be preserved by the test sequences the generator outputs. We implement this approach in a tool called Clouseau, and evaluate it on a diverse range of applications by integrating Clouseau's synthesized generators into property-based testing frameworks like QCheck and model-checking tools like P. In both settings, the generators synthesized by Clouseau are significantly more effective than the default testing strategy, and are competitive with state-of-the-art, handwritten solutions.