Trace-Guided Synthesis of Effectful Test Generators

TL;DR

This paper introduces a type-guided approach for synthesizing effectful test generators that leverage underapproximate behaviors to improve testing effectiveness.

Contribution

It presents a novel type system capturing underapproximate effect behaviors and implements a tool, Clouseau, for generating effective test sequences for effectful systems.

Findings

Clouseau's generators outperform default strategies in property-based testing.

Generated test sequences are competitive with handwritten solutions.

The approach effectively probes black-box effectful systems using symbolic traces.

Abstract

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.