Invariant testing is one of the essential techniques used to ensure that smart contracts maintain their core properties under all conditions. Given that smart contracts often manage and transfer millions of dollars in value, any flaw in their logic could lead to significant financial losses and negatively impact user trust.

In this blog post, we will discover the concept of invariant testing, discuss its significance for smart contracts, and provide practical examples of Invariant testing and Fuzzing.

Table of Contents

What is Invariant Testing?
Invariant Test for Buggy Token Contract
Why Invariant Testing is Important for Smart Contracts
What are the Differences between Invariant Testing and Fuzz Testing
Closing Thoughts

What is Invariant Testing?

Invariant testing is the procedure of ensuring that particular conditions, known as invariants, are valid all through the execution of a smart contract.

An invariant is a property that must always hold true no matter what state transitions or inputs are passed to the contract. For example, If suppose that we have an invariant such as the total supply of a token, The total supply should always equal the sum of balances of all accounts:

Total supply =∑(balance of each account)

Below, we will create a smart contract with a bug that an invariant test can uncover. The contract is designed to manage a token but has an issue with its transfer function that may lead to an incorrect total supply.

Buggy Token Contract

Invariant Test for Buggy Token Contract

We will use Foundry to write an invariant test that detects the issue with the transfer function.

1 - Set Up the Project

Initialize a new Foundry project and create the token contract:

forge init buggy-token

cd buggy-token

Add the contract code above to: src/BuggyToken.sol.

2 - Write the Invariant Test

Create the test file:

3 - Run the Tests

Execute the tests using Foundry:
forge test

4 - Explanation

1. BuggyToken Contract: This contract has a bug in the transfer function where only half of the intended amount is transferred to the recipient.

2. Invariant Test: The test checks if the total supply of tokens always equals the sum of balances of all accounts. This invariant test will fail due to the bug, revealing the discrepancy.

3. Additional Test: The test_Transfer function explicitly tests the transfer functionality, expecting a certain behavior that highlights the bug.

   
   

By running these tests, the invariant test will detect that the total supply does not match the sum of balances, uncovering the transfer bug.

Why Invariant Testing is Important for Smart Contracts

Smart contracts often manage significant assets, making their security and reliability crucial. Invariant testing helps identify vulnerabilities that unit tests and manual audits might miss by ensuring that key properties hold true under all conditions. This reduces the risk of bugs that could lead to financial losses.
Additionally, invariant testing proves to users and developers that the contract maintains its core properties consistently, improving trust and confidence in its operation.

1. Stronger Security: Invariant testing can uncover subtle bugs and vulnerabilities that might not be uncovered through standard unit tests or manual code security audits.
   
   

2. Comprehensive Coverage: Unlike unit tests that typically check specific functions and their expected outputs, invariant testing ensures the overall contract's behavior aligns with the defined invariants under all possible states. This provides a more thorough validation of the contract's logic.
   
   

3. Improved Reliability: By continuously validating that critical properties hold true, invariant testing helps ensure that the contract behaves as expected in all scenarios. This reduces the likelihood of unexpected behaviors or edge cases causing issues.
   
   

4. Increased Trust and Confidence: When users and developers see that a contract has undergone rigorous invariant testing, it builds confidence in its reliability and security. This is particularly important in blockchain applications, where trust is a fundamental component.

Differences between Invariant Testing and Fuzz Testing

Invariant Testing

Invariant testing involves defining certain conditions, or invariants, that must always be true for a smart contract. These tests are designed to validate that these conditions hold across all possible states. The primary goal is to ensure the logical correctness of the contract and that core properties remain intact under all circumstances.

Key Points:

• Focuses on ensuring invariants hold true.

• Validates logical correctness.

• Typically involves systematic checks against predefined conditions.

  
  

Fuzz Testing

Fuzz testing involves providing invalid, unexpected, or random inputs to a smart contract to discover bugs. It can be done in a stateless manner, where each input is independent, or statefully, where the contract state evolves over a series of transactions. The primary goal is to find edge cases and bugs that might not be evident through traditional testing methods like unit tests.

Key Points:

• Uses random inputs to test for bugs.

• Can be stateless or stateful.

• Aims to uncover edge cases.

Invariant Testing vs Fuzz Testing

Purpose:

• Invariant Testing: Ensures that specific properties always hold true.

• Fuzz Testing: Finds bugs and vulnerabilities through unexpected random inputs.

Approach:

• Invariant Testing: Systematic validation of predefined conditions.

• Fuzz Testing: Randomized input generation to uncover edge case issues.

Focus:

• Invariant Testing: Logical correctness and core properties (Invariants).

• Fuzz Testing: Edge cases.
  
  

Closing Thoughts

Invariant testing builds trust among users and developers, confirming that the contract behaves as expected under all conditions. While fuzz testing finds edge cases through random inputs, invariant testing systematically checks predefined conditions. Together, they provide a robust approach to smart contract testing, enhancing both security and reliability.