Create comprehensive MATLAB unit tests using the MATLAB Testing Framework. Use when generating test files, test cases, unit tests, test suites, or when the user requests testing for MATLAB code, functions, or classes.
Generates comprehensive MATLAB unit tests using the MATLAB Testing Framework. Use when creating test files, test cases, or when users request testing for MATLAB code, functions, or classes.
/plugin marketplace add matlab/skills/plugin install matlab-matlab-skills@matlab/skillsThis skill inherits all available tools. When active, it can use any tool Claude has access to.
This skill provides comprehensive guidelines for creating robust unit tests using the MATLAB Testing Framework. Generate test classes, test methods, and test suites following MATLAB best practices.
MATLAB supports multiple testing approaches:
classdef MyFunctionTest < matlab.unittest.TestCase
% Tests for myFunction
properties (TestParameter)
% Define parameters for parameterized tests
end
properties
% Test fixtures and shared data
end
methods (TestClassSetup)
% Runs once before all tests
end
methods (TestClassTeardown)
% Runs once after all tests
end
methods (TestMethodSetup)
% Runs before each test method
end
methods (TestMethodTeardown)
% Runs after each test method
end
methods (Test)
% Individual test methods
end
end
Test.m (e.g., myFunctionTest.m)tests/ directory or alongside source with Test suffixtestAdditionWithPositiveNumbersAlways use the appropriate assertion method:
verifyEqual(actual, expected) - Continues testing on failureassertEqual(actual, expected) - Stops testing on failure (legacy)verifyTrue(condition) - Verify boolean conditionverifyError(f, errorID) - Verify function throws errorverifyWarning(f, warningID) - Verify function issues warningverifyInstanceOf(actual, expectedClass) - Verify object typeverifySize(actual, expectedSize) - Verify array sizeverifyEmpty(actual) - Verify empty arrayFunction to test (add.m):
function result = add(a, b)
% ADD Add two numbers
result = a + b;
end
Test class (addTest.m):
classdef addTest < matlab.unittest.TestCase
% Tests for add function
methods (Test)
function testAddPositiveNumbers(testCase)
% Test addition of positive numbers
result = add(2, 3);
testCase.verifyEqual(result, 5);
end
function testAddNegativeNumbers(testCase)
% Test addition of negative numbers
result = add(-2, -3);
testCase.verifyEqual(result, -5);
end
function testAddMixedNumbers(testCase)
% Test addition of positive and negative
result = add(5, -3);
testCase.verifyEqual(result, 2);
end
function testAddZero(testCase)
% Test addition with zero
result = add(5, 0);
testCase.verifyEqual(result, 5);
end
function testAddArrays(testCase)
% Test element-wise addition of arrays
result = add([1 2 3], [4 5 6]);
testCase.verifyEqual(result, [5 7 9]);
end
end
end
classdef calculateAreaTest < matlab.unittest.TestCase
% Tests for calculateArea function with parameters
properties (TestParameter)
rectangleDims = struct(...
'small', struct('width', 2, 'height', 3, 'expected', 6), ...
'large', struct('width', 10, 'height', 20, 'expected', 200), ...
'unit', struct('width', 1, 'height', 1, 'expected', 1));
end
methods (Test)
function testRectangleArea(testCase, rectangleDims)
% Test rectangle area calculation
area = calculateArea(rectangleDims.width, rectangleDims.height);
testCase.verifyEqual(area, rectangleDims.expected);
end
end
end
classdef DataProcessorTest < matlab.unittest.TestCase
% Tests for DataProcessor class with setup/teardown
properties
TestData
TempFile
end
methods (TestMethodSetup)
function createTestData(testCase)
% Create test data before each test
testCase.TestData = rand(100, 5);
testCase.TempFile = tempname;
end
end
methods (TestMethodTeardown)
function deleteTestData(testCase)
% Clean up after each test
if isfile(testCase.TempFile)
delete(testCase.TempFile);
end
end
end
methods (Test)
function testDataLoading(testCase)
% Test data loading functionality
save(testCase.TempFile, 'data', testCase.TestData);
processor = DataProcessor(testCase.TempFile);
testCase.verifyEqual(processor.data, testCase.TestData);
end
function testDataNormalization(testCase)
% Test data normalization
processor = DataProcessor();
processor.data = testCase.TestData;
normalized = processor.normalize();
testCase.verifyLessThanOrEqual(max(normalized(:)), 1);
testCase.verifyGreaterThanOrEqual(min(normalized(:)), 0);
end
end
end
classdef validateInputTest < matlab.unittest.TestCase
% Tests for validateInput function
methods (Test)
function testValidInput(testCase)
% Test valid input passes
testCase.verifyWarningFree(@() validateInput(5));
end
function testNegativeInputError(testCase)
% Test negative input throws error
testCase.verifyError(@() validateInput(-5), 'MATLAB:validators:mustBePositive');
end
function testNonNumericInputError(testCase)
% Test non-numeric input throws error
testCase.verifyError(@() validateInput('text'), 'MATLAB:validators:mustBeNumeric');
end
function testEmptyInputError(testCase)
% Test empty input throws error
testCase.verifyError(@() validateInput([]), 'MATLAB:validators:mustBeNonempty');
end
end
end
project/
├── src/
│ ├── myFunction.m
│ └── MyClass.m
└── tests/
├── myFunctionTest.m
└── MyClassTest.m
Run all tests in directory:
results = runtests('tests')
Run specific test class:
results = runtests('myFunctionTest')
Run specific test method:
results = runtests('myFunctionTest/testAddPositiveNumbers')
Generate test suite:
suite = testsuite('tests');
results = run(suite);
With coverage report:
import matlab.unittest.TestRunner
import matlab.unittest.plugins.CodeCoveragePlugin
runner = TestRunner.withTextOutput;
runner.addPlugin(CodeCoveragePlugin.forFolder('src'));
results = runner.run(testsuite('tests'));
For floating-point comparisons, use tolerance:
% Absolute tolerance
testCase.verifyEqual(actual, expected, 'AbsTol', 1e-10);
% Relative tolerance
testCase.verifyEqual(actual, expected, 'RelTol', 1e-6);
% Both
testCase.verifyEqual(actual, expected, 'AbsTol', 1e-10, 'RelTol', 1e-6);
Use assumptions to skip tests when prerequisites aren't met:
function testPlotting(testCase)
% Skip test if not running in graphical environment
testCase.assumeTrue(usejava('desktop'), 'Requires desktop environment');
% Test code here
fig = figure;
plot(1:10);
testCase.verifyInstanceOf(fig, 'matlab.ui.Figure');
close(fig);
end
Tag tests for selective execution:
methods (Test, TestTags = {'Unit'})
function testBasicOperation(testCase)
% Fast unit test
end
end
methods (Test, TestTags = {'Integration', 'Slow'})
function testDatabaseConnection(testCase)
% Slower integration test
end
end
Run tagged tests:
% Run only Unit tests
suite = testsuite('tests', 'Tag', 'Unit');
results = run(suite);
For testing code with dependencies:
function testWithMock(testCase)
% Create mock object
import matlab.mock.TestCase
[mock, behavior] = testCase.createMock(?MyInterface);
% Define behavior
testCase.assignOutputsWhen(withAnyInputs(behavior.methodName), expectedOutput);
% Use mock in test
result = functionUnderTest(mock);
testCase.verifyEqual(result, expectedValue);
end
Test execution time:
function testPerformance(testCase)
% Test function executes within time limit
tic;
result = expensiveFunction(largeData);
elapsedTime = toc;
testCase.verifyLessThan(elapsedTime, 1.0, ...
'Function should complete within 1 second');
end
Before finalizing tests, verify:
Test.mmatlab.unittest.TestCaseverifyErrorfunction testCalculation(testCase)
% Arrange - Set up test data
input1 = 5;
input2 = 3;
expected = 8;
% Act - Execute the code under test
actual = myFunction(input1, input2);
% Assert - Verify the result
testCase.verifyEqual(actual, expected);
end
% Use access to test private methods
classdef MyClassTest < matlab.unittest.TestCase
methods (Test)
function testPrivateMethod(testCase)
obj = MyClass();
% Access private method
result = obj.privateMethod(testCase);
testCase.verifyEqual(result, expectedValue);
end
end
end
function testStaticMethod(testCase)
% Test static method without instantiation
result = MyClass.staticMethod(input);
testCase.verifyEqual(result, expected);
end
Issue: Tests not discovered
Test.m and class inherits from matlab.unittest.TestCaseIssue: Floating-point comparison failures
'AbsTol' or 'RelTol' parameters with verifyEqualIssue: Tests affecting each other
Issue: Slow test execution
doc matlab.unittest.TestCase for complete assertion referencedoc matlab.unittest.fixtures for advanced fixture usagedoc matlab.mock for mocking framework documentationThis skill should be used when the user asks to "create a slash command", "add a command", "write a custom command", "define command arguments", "use command frontmatter", "organize commands", "create command with file references", "interactive command", "use AskUserQuestion in command", or needs guidance on slash command structure, YAML frontmatter fields, dynamic arguments, bash execution in commands, user interaction patterns, or command development best practices for Claude Code.
This skill should be used when the user asks to "create an agent", "add an agent", "write a subagent", "agent frontmatter", "when to use description", "agent examples", "agent tools", "agent colors", "autonomous agent", or needs guidance on agent structure, system prompts, triggering conditions, or agent development best practices for Claude Code plugins.
This skill should be used when the user asks to "create a hook", "add a PreToolUse/PostToolUse/Stop hook", "validate tool use", "implement prompt-based hooks", "use ${CLAUDE_PLUGIN_ROOT}", "set up event-driven automation", "block dangerous commands", or mentions hook events (PreToolUse, PostToolUse, Stop, SubagentStop, SessionStart, SessionEnd, UserPromptSubmit, PreCompact, Notification). Provides comprehensive guidance for creating and implementing Claude Code plugin hooks with focus on advanced prompt-based hooks API.