Objective:
Create a library extending ScalaCheck to allow stateful composition of generators with complex dependencies and constraints.
Key Requirements:
1. Support for deep, nested generator compositions (e.g., A-B-C-D).
2. Allow constraints between non-adjacent generators (e.g., A-D).
3. Enable sequential generation of data to maintain state consistency.
4. Permit regeneration or selection of specific child generators without regenerating the entire tree.
Proposed Approach:
Implement a StateT-like mechanism, potentially incorporating state machines, to manage the stateful generation process. This approach aims to:
– Ensure proper sequencing of generator execution.
– Maintain state information throughout the generation tree.
– Allow for targeted regeneration of specific subtrees or leaves.
Distinctions:
This problem focuses on stateful generation, which differs from traditional stateful testing. The goal is to create a framework for composing generators that can adapt based on the current state and previously generated values.
Question:
Are there any existing solutions or research addressing this specific problem of stateful composition in property-based testing generators?
This is an interesting and complex problem in the field of property-based testing. To my knowledge, there isn’t a widely-adopted solution that fully addresses all aspects of stateful composition for property-based testing generators as you’ve described. However, there are some existing approaches and research that touch on related concepts. Let me break this down:
1. Existing Solutions:
a) ScalaCheck itself has some support for stateful testing through its `Commands` trait, but this is more focused on testing stateful systems rather than composing stateful generators.
b) The `hedgehog` library for Haskell and its ports to other languages (including Scala) provide some capabilities for creating interdependent generators, though not to the full extent you’re describing.
c) The `fast-check` library for JavaScript/TypeScript has a concept of “commands” that allow for some stateful generation, but again, it’s not as comprehensive as your proposed approach.
2. Related Research:
a) There has been some academic work on improving property-based testing generators, such as the paper “Improving Random Testing through Dynamic Dependence Analysis” by Pacheco et al. This doesn’t directly address stateful composition but explores related concepts.
b) The concept of “Stateful Quickcheck” has been explored in some Haskell-oriented discussions and blog posts, but these typically focus more on testing stateful systems rather than composing stateful generators.
3. Potential Starting Points:
a) The `StateT` monad transformer in functional programming could indeed be a good starting point for managing state across generators.
b) Some ideas from Effect Systems might be applicable, particularly in managing the dependencies between generators.
c) The concept of Applicative Functors with dependencies, as explored in some functional programming research, could potentially be adapted to this problem.
Your proposed approach seems to be pushing the boundaries of what’s currently available in property-based testing libraries. The combination of deep nesting, non-adjacent constraints, sequential generation with state consistency, and selective regeneration presents a unique set of challenges.
To fully realize this concept, you might need to:
1. Design a custom DSL (Domain Specific Language) for defining these stateful generator compositions.
2. Implement a custom execution engine that can traverse the generator tree while maintaining state.
3. Develop a constraint solving system that can handle both adjacent and non-adjacent constraints.
4. Create a caching or memoization system to allow for efficient regeneration of subtrees.
This is definitely an advanced topic in property-based testing, and implementing a full solution would likely be a significant undertaking. It could potentially be a valuable contribution to the field if developed and open-sourced.
Would you like me to elaborate on any specific aspect of this problem or potential approaches to solving it?