Unfuzzed Local Variables in Test Functions
Overview
- Severity: Low
- Confidence: High
- Affected Versions: All
What are Unfuzzed Local Variables?
In the context of property-based testing or fuzzing, unfuzzed local variables are those declared within a test function but not initialized with random or fuzzed input. This can lead to incomplete test coverage and potentially missed edge cases.
Why are Unfuzzed Local Variables Problematic?
Unfuzzed local variables in test functions can lead to several issues:
- Reduced test coverage due to constant or predictable values
- Missed edge cases that could reveal bugs or vulnerabilities
- False sense of security from seemingly comprehensive tests
- Inefficient use of fuzzing capabilities
- Potential for overlooking critical contract behaviors under varied inputs
Technical Example of Unfuzzed Local Variables
pragma solidity ^0.8.0;
import "./test.sol";
contract TokenTest is Test {
Token token;
function setUp() public {
token = new Token();
}
function testTransfer(address to, uint256 amount) public {
uint256 initialBalance = 1000; // Unfuzzed local variable
token.mint(address(this), initialBalance);
token.transfer(to, amount);
assertEq(token.balanceOf(to), amount);
}
}
In this example, `initialBalance` is a local variable that is not fuzzed. This means the test will always start with the same balance, potentially missing issues that could arise with different initial balances.
Technical Example of Properly Fuzzed Variables
pragma solidity ^0.8.0;
import "./test.sol";
contract TokenTest is Test {
Token token;
function setUp() public {
token = new Token();
}
function testTransfer(address to, uint256 amount, uint256 initialBalance) public {
vm.assume(initialBalance >= amount); // Ensure valid test conditions
token.mint(address(this), initialBalance);
token.transfer(to, amount);
assertEq(token.balanceOf(to), amount);
assertEq(token.balanceOf(address(this)), initialBalance - amount);
}
}
In this improved version, `initialBalance` is now a parameter of the test function, allowing it to be fuzzed. This ensures that the test covers a wide range of initial balance scenarios, potentially uncovering edge cases or bugs that weren't visible with a fixed initial balance.