unclebob/acceptance-pipeline-specification — explained in plain English
Analysis updated 2026-05-18
Design a pipeline that converts Gherkin feature files into a standardized JSON intermediate format
Auto-generate executable acceptance tests from that JSON representation in any language
Use mutation testing to check whether generated tests actually catch broken behavior
Give an AI coding agent a reproducible spec for wiring up acceptance testing in a new project
| unclebob/acceptance-pipeline-specification | chaelsoo/hollow | ingar30/reviewer | |
|---|---|---|---|
| Stars | 80 | 80 | 80 |
| Language | — | C | Python |
| Setup difficulty | moderate | moderate | moderate |
| Complexity | 3/5 | 3/5 | 3/5 |
| Audience | developer | developer | researcher |
Figures from each repo's GitHub metadata at analysis time.
This is a specification document, not a runnable tool, you implement it yourself in your chosen language.
This repository defines a specification, a detailed blueprint, for building an automated acceptance-testing pipeline. An acceptance test checks whether a software application actually does what it promises from the user's perspective, as opposed to just checking that individual code pieces work in isolation. The pipeline starts from a Gherkin feature file, which is a structured plain-English way of describing how a system should behave using "Given/When/Then" sentences. The specification defines how to parse that file into a standardized JSON data structure, then how to automatically generate real executable tests from that data, run those tests, and report results. A second operating mode, called mutation testing, deliberately changes the example values in the feature file to check whether the generated tests are sensitive enough to actually catch problems, a way of testing your tests. The spec is intentionally language-agnostic and project-neutral, meaning it can be implemented in Python, Java, TypeScript, or any other language. It defines the required components (a Gherkin parser, a JSON intermediary, a test generator, a mutator, and convenience scripts), the expected directory layout, command-line interfaces, exit codes, and the exact JSON format for the intermediate representation. This would be used by teams or AI coding agents who want to install a reproducible, portable acceptance-testing workflow in any new project without reinventing the architecture each time. The author is unclebob, known in the industry for writing about software craftsmanship.
A language-agnostic specification for building an automated pipeline that turns Gherkin acceptance tests into runnable, mutation-tested code.
License is not specified in the description.
Setup difficulty is rated moderate, with roughly 1h+ to a first successful run.
Mainly developer.
This repo across BitVibe Labs
Verify against the repo before relying on details.