Counterexample To Test Generator logo

Counterexample To Test Generator

Community
ArabelaTso
counterexample-to-test-generator

Automatically generates executable test cases from model checking counterexample traces. Translates abstract counterexample states and transitions into concrete test inputs, execution steps, and assertions that reproduce property violations. Use when working with model checker outputs (SPIN, CBMC, NuSMV, TLA+, Java PathFinder, etc.) and needing to create regression tests, validate bug fixes, or reproduce verification failures in executable test suites.

Overview

PublisherArabelaTso
RepositorySkills-4-SE
Skill namecounterexample-to-test-generator
Stars
258
Forks
25
Bundled files
6
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 6 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by ArabelaTso on GitHub. Read the source before you install it.

Installation

Install the Counterexample To Test Generator AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/ArabelaTso/Skills-4-SE/tree/main/skills/counterexample-to-test-generator
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/ArabelaTso/Skills-4-SE.git /tmp/Skills-4-SE
mkdir -p .claude/skills
cp -r /tmp/Skills-4-SE/skills/counterexample-to-test-generator .claude/skills/counterexample-to-test-generator
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Counterexample To Test Generator in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Counterexample To Test Generator on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Counterexample To Test Generator is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Counterexample To Test Generator

Overview

This skill transforms counterexample traces from model checkers into executable test cases that reliably reproduce property violations. It bridges formal verification and testing by mapping abstract states to concrete values and generating runnable tests with clear traceability from counterexample steps to test logic.

Workflow

Step 1: Analyze Inputs

Gather and understand the counterexample trace and program:

  1. Identify the model checker format: Determine which tool produced the counterexample (SPIN, CBMC, NuSMV, TLA+, JPF, etc.). See references/model_checker_formats.md for format details.

  2. Extract key information:

    • Initial state values
    • Sequence of transitions/steps
    • Variable values at each step
    • Property violation point
    • Error condition or assertion failure
  3. Understand the program structure:

    • Entry points and function signatures
    • Input parameters and their types
    • State variables involved in the trace
    • Control flow relevant to the counterexample

Step 2: Map Abstract States to Concrete Values

Translate the counterexample's abstract representation into concrete test inputs:

  1. Determine concrete values for abstract state variables:

    • Map symbolic values to concrete instances
    • Resolve non-deterministic choices to specific values
    • Handle ranges and constraints from the model
  2. Identify input sequences:

    • Extract the sequence of function calls or operations
    • Determine parameter values for each call
    • Identify timing or ordering constraints
  3. Handle environment assumptions:

    • External inputs or system calls
    • Concurrency or scheduling decisions
    • Resource states (files, network, memory)

Step 3: Generate Test Structure

Create the test case framework in the target language:

  1. Choose test framework based on the program language:

    • C/C++: Google Test, CUnit, Check
    • Java: JUnit, TestNG
    • Python: pytest, unittest
    • C#: NUnit, xUnit
  2. Structure the test:

    • Setup phase: Initialize state to match counterexample start
    • Execution phase: Replay the counterexample sequence
    • Assertion phase: Verify the property violation occurs
  3. Add traceability comments: Map each test step to counterexample steps for debugging and maintenance.

Step 4: Implement Test Logic

Write the executable test code:

  1. Setup code:

    // Initialize variables to counterexample initial state
    // Set up test fixtures or mocks
    // Configure environment (if needed)
  2. Execution sequence:

    // Step 1 (CE line X): [description]
    // Execute operation with concrete values
    
    // Step 2 (CE line Y): [description]
    // Execute next operation
  3. Assertions:

    // Verify property violation (CE line Z)
    // Assert expected failure condition
    // Check final state matches counterexample

Step 5: Generate Output

Produce the complete test case with documentation:

  1. Test file: Complete, compilable/runnable test code
  2. Mapping document: Table linking counterexample steps to test lines
  3. Execution instructions: How to compile and run the test
  4. Expected behavior: What the test should demonstrate (failure reproduction)

Example Workflow

Input: SPIN counterexample showing a deadlock in a concurrent system

Output:

c
// test_deadlock.c - Reproduces deadlock from SPIN counterexample trail
#include <pthread.h>
#include <assert.h>

// Counterexample mapping:
// CE Step 1-2: Thread 1 acquires lock A
// CE Step 3-4: Thread 2 acquires lock B
// CE Step 5: Thread 1 waits for lock B (blocks)
// CE Step 6: Thread 2 waits for lock A (deadlock)

void* thread1_func(void* arg) {
    pthread_mutex_lock(&lock_a);  // CE Step 1
    sleep(1);                      // CE Step 2 (timing)
    pthread_mutex_lock(&lock_b);  // CE Step 5 (blocks)
    // ... rest of test
}

void test_deadlock_scenario() {
    // Setup: Initialize locks (CE initial state)
    pthread_mutex_init(&lock_a, NULL);
    pthread_mutex_init(&lock_b, NULL);

    // Execute: Create threads in counterexample order
    pthread_create(&t1, NULL, thread1_func, NULL);
    pthread_create(&t2, NULL, thread2_func, NULL);

    // This test will hang, demonstrating the deadlock
    pthread_join(t1, NULL);  // Will timeout
}

Best Practices

  1. Minimize test complexity: Generate the simplest test that reproduces the violation
  2. Preserve causality: Maintain the exact sequence from the counterexample
  3. Make violations obvious: Use clear assertions and error messages
  4. Add context: Include comments explaining the property being violated
  5. Handle non-determinism: Document any assumptions made when concretizing values
  6. Test the test: Verify the generated test actually fails as expected

Common Challenges

Challenge: Counterexample uses symbolic values without concrete bounds Solution: Use representative values from the domain, document the choice

Challenge: Trace involves complex timing or scheduling Solution: Use synchronization primitives or explicit delays to enforce ordering

Challenge: Program state is partially specified in counterexample Solution: Initialize unspecified variables to default/neutral values

Challenge: Counterexample is very long Solution: Identify the minimal prefix that still triggers the violation

References

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Counterexample To Test Generator AI skill do?

Automatically generates executable test cases from model checking counterexample traces. Translates abstract counterexample states and transitions into concrete test inputs, execution steps, and assertions that reproduce property violations. Use when working with model checker outputs (SPIN, CBMC, NuSMV, TLA+, Java PathFinder, etc.) and needing to create regression tests, validate bug fixes, or reproduce verification failures in executable test suites.

Why use Counterexample To Test Generator on TypingMind?

Because you install it once and use it with any model. Counterexample To Test Generator is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Counterexample To Test Generator in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/ArabelaTso/Skills-4-SE/tree/main/skills/counterexample-to-test-generator. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Counterexample To Test Generator?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Counterexample To Test Generator?

As many as you like. As long as a model supports skills, you can use Counterexample To Test Generator with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Counterexample To Test Generator AI skill free?

Yes. It is published on GitHub by ArabelaTso under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇