Test Anti-Pattern Detection

Quick, pragmatic analysis of .NET test code for anti-patterns and quality issues that undermine test reliability, maintainability, and diagnostic value.

When to Use

• User asks to review test quality or find test smells
• User wants to know why tests are flaky or unreliable
• User asks "are my tests good?" or "what's wrong with my tests?"
• User requests a test audit or test code review
• User wants to improve existing test code

When Not to Use

• User wants to write new tests from scratch (use writing-mstest-tests)
• User wants direct implementation fixes in MSTest code rather than a diagnostic review (use writing-mstest-tests)
• User asks to fix swapped Assert.AreEqual argument order (use writing-mstest-tests)
• User asks to convert DynamicData from IEnumerable<object[]> to ValueTuple (use writing-mstest-tests)
• User wants to run or execute tests (use run-tests)
• User wants to migrate between test frameworks or versions (use migration skills)
• User wants to measure code coverage (out of scope)
• User wants a deep formal test smell audit with academic taxonomy and extended catalog (use exp-test-smell-detection)

Inputs

Input	Required	Description
Test code	Yes	One or more test files or classes to analyze
Production code	No	The code under test, for context on what tests should verify
Specific concern	No	A focused area like "flakiness" or "naming" to narrow the review

Workflow

Step 1: Gather the test code

Read the test files the user wants reviewed. If the user points to a directory or project, scan for all test files using the framework-specific markers in the dotnet-test-frameworks skill (e.g., [TestClass], [Fact], [Test]).

If production code is available, read it too -- this is critical for detecting tests that are coupled to implementation details rather than behavior.

Step 2: Scan for anti-patterns

Check each test file against the anti-pattern catalog below. Report findings grouped by severity.

Critical -- Tests that give false confidence

Anti-Pattern	What to Look For
No assertions	Test methods that execute code but never assert anything. A passing test without assertions proves nothing.
Swallowed exceptions	try { ... } catch { } or catch (Exception) without rethrowing or asserting. Failures are silently hidden.
Assert in catch block only	try { Act(); } catch (Exception ex) { Assert.Fail(ex.Message); } -- use Assert.ThrowsException or equivalent instead. The test passes when no exception is thrown even if the result is wrong.
Always-true assertions	Assert.IsTrue(true), Assert.AreEqual(x, x), or conditions that can never fail.
Commented-out assertions	Assertions that were disabled but the test still runs, giving the illusion of coverage.

High -- Tests likely to cause pain

Anti-Pattern	What to Look For
Flakiness indicators	Thread.Sleep(...), Task.Delay(...) for synchronization, DateTime.Now/DateTime.UtcNow without abstraction, Random without a seed, environment-dependent paths.
Test ordering dependency	Static mutable fields modified across tests, [TestInitialize] that doesn't fully reset state, tests that fail when run individually but pass in suite (or vice versa).
Over-mocking	More mock setup lines than actual test logic. Verifying exact call sequences on mocks rather than outcomes. Mocking types the test owns. For a deep mock audit, use exp-mock-usage-analysis.
Implementation coupling	Testing private methods via reflection, asserting on internal state, verifying exact method call counts on collaborators instead of observable behavior.
Broad exception assertions	Assert.ThrowsException<Exception>(...) instead of the specific exception type. Also: [ExpectedException(typeof(Exception))].

Medium -- Maintainability and clarity issues

Anti-Pattern	What to Look For
Poor naming	Test names like Test1, TestMethod, names that don't describe the scenario or expected outcome. Good: Add_NegativeNumber_ThrowsArgumentException.
Magic values	Unexplained numbers or strings in arrange/assert: Assert.AreEqual(42, result) -- what does 42 mean?
Duplicate tests	Three or more test methods with near-identical bodies that differ only in a single input value. Should be data-driven ([DataRow], [Theory], [TestCase]). For a detailed duplication analysis, use exp-test-maintainability. Note: Two tests covering distinct boundary conditions (e.g., zero vs. negative) are NOT duplicates -- separate tests for different edge cases provide clearer failure diagnostics and are a valid practice.
Giant tests	Test methods exceeding ~30 lines or testing multiple behaviors at once. Hard to diagnose when they fail.
Assertion messages that repeat the assertion	Assert.AreEqual(expected, actual, "Expected and actual are not equal") adds no information. Messages should describe the business meaning.
Missing AAA separation	Arrange, Act, Assert phases are interleaved or indistinguishable.

Low -- Style and hygiene

Anti-Pattern	What to Look For
Unused test infrastructure	[TestInitialize]/[SetUp] that does nothing, test helper methods that are never called.
IDisposable not disposed	Test creates HttpClient, Stream, or other disposable objects without using or cleanup.
Console.WriteLine debugging	Leftover Console.WriteLine or Debug.WriteLine statements used during test development.
Inconsistent naming convention	Mix of naming styles in the same test class (e.g., some use Method_Scenario_Expected, others use ShouldDoSomething).

Step 3: Calibrate severity honestly

Before reporting, re-check each finding against these severity rules:

• Critical/High: Only for issues that cause tests to give false confidence or be unreliable. A test that always passes regardless of correctness is Critical. Flaky shared state is High.
• Medium: Only for issues that actively harm maintainability -- 5+ nearly-identical tests, truly meaningless names like Test1.
• Low: Cosmetic naming mismatches, minor style preferences, assertion messages that could be better. When in doubt, rate Low.
• Not an issue: Separate tests for distinct boundary conditions (zero vs. negative vs. null). Explicit per-test setup instead of [TestInitialize] (this improves isolation). Tests that are short and clear but could theoretically be consolidated.

IMPORTANT: If the tests are well-written, say so clearly up front. Do not inflate severity to justify the review. A review that finds zero Critical/High issues and only minor Low suggestions is a valid and valuable outcome. Lead with what the tests do well.

Step 4: Report findings

Present findings in this structure:

1. Summary -- Total issues found, broken down by severity (Critical / High / Medium / Low). If tests are well-written, lead with that assessment.
2. Critical and High findings -- List each with:
   • The anti-pattern name
   • The specific location (file, method name, line)
   • A brief explanation of why it's a problem
   • A concrete fix (show before/after code when helpful)
3. Medium and Low findings -- Summarize in a table unless the user wants full detail
4. Positive observations -- Call out things the tests do well (sealed class, specific exception types, data-driven tests, clear AAA structure, proper use of fakes, good naming). Don't only report negatives.

Step 5: Prioritize recommendations

If there are many findings, recommend which to fix first:

1. Critical -- Fix immediately, these tests may be giving false confidence
2. High -- Fix soon, these cause flakiness or maintenance burden
3. Medium/Low -- Fix opportunistically during related edits

Validation

• Every finding includes a specific location (not just a general warning)
• Every Critical/High finding includes a concrete fix
• Report covers all categories (assertions, isolation, naming, structure)
• Positive observations are included alongside problems
• Recommendations are prioritized by severity

Common Pitfalls

Pitfall	Solution
Reporting style issues as critical	Naming and formatting are Medium/Low, never Critical
Suggesting rewrites instead of targeted fixes	Show minimal diffs -- change the assertion, not the whole test
Flagging intentional design choices	If Thread.Sleep is in an integration test testing actual timing, that's not an anti-pattern. Consider context.
Inventing false positives on clean code	If tests follow best practices, say so. A review finding "0 Critical, 0 High, 1 Low" is perfectly valid. Don't inflate findings to justify the review.
Flagging separate boundary tests as duplicates	Two tests for zero and negative inputs test different edge cases. Only flag as duplicates when 3+ tests have truly identical bodies differing by a single value.
Rating cosmetic issues as Medium	Naming mismatches (e.g., method name says ArgumentException but asserts ArgumentOutOfRangeException) are Low, not Medium -- the test still works correctly.
Ignoring the test framework	xUnit uses [Fact]/[Theory], NUnit uses [Test]/[TestCase], MSTest uses [TestMethod]/[DataRow] -- use correct terminology
Missing the forest for the trees	If 80% of tests have no assertions, lead with that systemic issue rather than listing every instance