falsegreen 0.8.1

Find unit tests that give false positives: green tests that protect nothing, and tests that pass while asserting the wrong expected value.

falsegreen

One problem, one tool: the false positive. falsegreen finds Python/pytest tests that pass green without protecting anything - tests that let broken code through because the assertion is empty, always true, never runs, or checks the wrong thing.

A test that tells you a broken program is safe is worse than no test at all. AI coding assistants produce these at scale. The tool catches them before they merge.

The scanner is a zero-dependency AST pass. It validates each test against 47 active false-positive codes, patterns a parser can prove: an assertion that never runs, a check that is empty or always true, a swallowed exception, a mock assertion with a typo, a check stranded in dead code. HIGH findings block the commit; LOW ones warn. A third group (diagnostic and coupling, six codes) can be enabled per project for informational checks that do not affect the exit code. The semantic layer, intent-based patterns no static tool can see, lives in falsegreen-skill, the LLM companion covering Python and other languages.

The checks are grounded in the rotten-green-test research (Soares 2023; Delplanque et al., ICSE 2019) and cross-walked against the published test-smell catalog. See CREDITS.md.

The falsegreen family (install the one for your stack):

Tool	Stack	Install	Package
falsegreen	Python / pytest	pip install falsegreen	PyPI
falsegreen-js	JS / TS	npm i -D falsegreen-js (npx falsegreen-js)	npm
robotframework-falsegreen	Robot Framework	pip install robotframework-falsegreen	PyPI
falsegreen-skill	semantic LLM pass	npx falsegreen-skill analyze <path>	npm

Install: pip install falsegreen. Pre-commit hook also available (see below). LLM semantic pass: falsegreen-skill.

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Table of contents

• Why this exists
• The methodology
• What it detects
• Codes the scanner does not detect
• Diagnostic and coupling codes
• The two layers
• Install and use
  • 1. CLI (pip)
  • 2. Pre-commit hook
  • 3. Semantic pass (multi-language)
• Configuration
• How it compares
• Project layout
• Contributing, security, license

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Why this exists

Coverage tells you which lines ran. It does not tell you whether anything was checked. A suite can report 90% coverage while most of those tests assert nothing real - the green bar is a comfort, not a guarantee.

The danger is not a test that fails. It is a test that passes when it should not.

falsegreen targets that one problem. It is not a style linter and not a coverage tool. It asks one question per test: is there a way for the code to be wrong and this test to stay green? If yes, the test is not protecting what it claims.

This matters more now that a large share of tests come from AI assistants. The common machine-written failure modes are exactly the patterns here: assertion roulette, mocking the unit under test, asserting the value you fed the mock, copying the expected value from the current output. They look thorough. They pass. falsegreen is the second reader that asks whether they actually verify anything.

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The methodology

One rule drives everything: a test is only useful if it fails when the code breaks. If you have never seen a test go red, you do not know that it tests anything.

The patterns are organized into five families:

• A. The test never checks anything. The assertion is skipped, missing, swallowed, or the test is never collected by the runner.
• B. The check is weak or always true. It accepts almost any output, or it is true by construction.
• C. The test checks itself, not the program. It mocks the thing under test, asserts the value it configured, or re-implements the production logic as its own answer key.
• D. Green depends on outside factors. Time, randomness, test order, a fixed sleep.
• E. The test passes but checks the wrong thing. The assertion runs against a real result, yet the expected value contradicts what the code should do, so the test freezes a bug.

Family E is why the project has a semantic layer. It carries the core principle: the expected value must come from an independent oracle, not from the code's current output. The oracle hierarchy, highest first: explicit spec or requirement, documented contract (docstring, types, API), independent human judgment, current code. Code is the lowest-priority oracle. Treating it as the highest is how you rubber-stamp a bug.

The plain-language guide, with a real-world analogy and before/after for each case, is in docs/guide.md. The full detection reference lives in falsegreen-skill.

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What it detects

The scanner ships 47 active false-positive codes across the five families, plus CC (commented-out assert). HIGH findings block a commit; LOW ones warn. Cases that require reading production intent (10, 11, 12, 15, 18) need the semantic layer.

#	Case	Why it fools you	Code	Conf
1	assert inside an if/for that may not run	check silently skips	C1	LOW
2	Test with no assertion at all	proves only it did not crash	C2/C2b	HIGH/LOW
3	assert inside try whose except swallows it	failure discarded	C3	HIGH
4	Test the runner never collects	vanishes from the count	C4/C4b	HIGH/LOW
5	Always-true check (assert True, non-empty tuple, or True)	passes by construction	C5	HIGH
6	Weak check (truthiness, len > 0, "x" in str(...))	accepts almost anything	C6	LOW
7	Compares a value to itself	true by construction	C7	HIGH
8	Exact equality on a float	fails on rounding, not bugs	C8	LOW
9	pytest.raises(Exception) too broad	accepts the wrong error	C9	LOW
10	Mocks the unit under test	tests the mock, not the code	semantic	-
11	Asserts the value fed to the mock	an echo, not a result	semantic	-
12	Re-implements the production formula	both agree on the same wrong number	semantic	-
13	Mock assertion misspelled / not called	becomes a no-op	C13/C13b	HIGH/LOW
14	Golden/snapshot written from the output	records today's bug as correct	C14	LOW
15	Passes only if another test ran first	borrowed state	semantic	-
16	Depends on time, randomness, or a sleep	passes or fails by luck	C16	LOW
17	skip inside a broad except	turns red into yellow	C17	HIGH
18	Expected value contradicts what code should do	freezes a bug as correct	semantic	-

Six codes cover patterns added after the original eighteen:

Code	Pattern	Why it fools you	Family	Conf
C18	Compares str()/repr()/f-string to literal	checks formatting, not the value	B	LOW
C19	pytest.raises wraps more than one call	earlier line raises; target never reached	A	LOW
C20	assert in dead code after return/raise/fail()	never runs	A	HIGH
C21	Every assert is conditional, none unconditional	false condition passes the whole test	A	LOW
C22	async test asserts but never awaits the unit	checks an un-awaited coroutine	A	off
C23	Opens a real file at a literal hard-coded path	binds test to a layout; often a credential outside the repo (Mystery Guest)	D	LOW

Eleven additional codes covering the most common patterns in real test suites:

Code	Pattern	Conf
C25	@pytest.mark.xfail without strict=True — XPASS silently accepted	LOW
C27	try/except/pass used instead of pytest.raises	HIGH
C28	pytest.raises binding declared but exception content never inspected	LOW
C29	os.environ mutated directly in a test — state leaks between tests	LOW
C30	responses.add() / httpretty.register_uri() without activating the interceptor	LOW
C31	capsys.readouterr() result never asserted	LOW
C32	@pytest.mark.skip without reason=	LOW
C33	sklearn / ML metric computed but never asserted	LOW
C34	Suboptimal assert form — pytest provides a clearer, more idiomatic alternative	LOW
C35	Retry/flaky decorator masks flaky behaviour instead of fixing the root cause	LOW
C36	pytest.fail() with no reason argument — failure message is empty	LOW
C37	Duplicate case in @pytest.mark.parametrize — same argument set runs twice	LOW
CC	Commented-out assert	LOW

More from the consolidated catalog:

Code	Pattern	Conf
C2c	self.subTest(...) block wraps work but asserts nothing — the subTest analogue of an empty test	LOW
C6b	Assertion coupled to positional argument layout — breaks on a benign reorder, not a bug	LOW
C6c	Asserts a mock's call_count truthiness — only that it was called, not how many times	LOW
C8b	Approximate-equality with no explicit tolerance (assertAlmostEqual, == pytest.approx()) — the default tolerance hides a wrong value	LOW
C11a	Self-confirming literal — the expected value is assigned by the test itself	LOW
C24	Module-global mutable state shared across tests — borrowed state, not isolation	LOW
C38	Two test functions share a name — the later one silently overrides the first	HIGH
C39	Test returns a comparison instead of asserting it — pytest ignores the value	HIGH
C41	Assertion on an in-place method that returns None (assert not lst.sort()) — trivially satisfied	LOW
C42	assert on a generator expression or lambda — the object is always truthy	HIGH
C43	pytest.skip() after test logic — the checks below it never run	LOW
C44	Numeric tautology (len(x) >= 0, abs(x) >= 0, a mock's call_count >= 0) — always true	HIGH
C45	Empty @pytest.mark.parametrize list — the test is generated with zero cases	HIGH
C48	Dark patch — the test forces a test-mode flag (os.environ["TESTING"], settings.TESTING) then asserts, exercising the product's test-only branch	LOW
C49	pytest.warns / assertWarns / deprecated_call wraps more than one call — an unrelated earlier line may warn while the target never does (warns sibling of C19)	LOW
C50	caplog / assertLogs output captured but never asserted — the capture has no effect on pass/fail (logging sibling of C31)	LOW
C51	Empty-bodied pytest.raises / warns context — no call inside the block, so the call that should raise is never made	HIGH
C52	Membership self-confirmation — assert x in {x}, the collection is built from the subject so membership is true by construction (membership variant of C7)	LOW
C55	Assertion compares two mock-rooted values — assert m.foo == m.bar, both sides are the test's own doubles not the SUT	LOW

Codes the scanner does not detect

The static layer is close to saturated. A handful of catalog codes are deliberately left out because a per-file AST pass cannot judge them without a high false-positive rate, or because they are not a per-file property at all. They are listed here so the gap is honest, not hidden. The reasoning follows the consolidated catalog.

High false-positive without deeper analysis (left to the semantic pass).

• C40 (assert on a Mock attribute with no spec, always truthy): without spec or autospec analysis the false-positive rate is high, since the same shape is a valid check on a real object. The concept lives in the skill (Family F7).
• C46 (real network or database call with no double): legitimate at the integration level, where crossing the boundary is the point. Flagging it per file, without knowing the test's layer, is a high false-positive. It belongs to the skill and the project layer.
• C47 (assertion depends on dict or set ordering): most collections are used deterministically, so flagging unordered-vs-sequence comparisons fires far too often. It stays a note in the skill.

Runtime and culture (not a per-file property). The PL series is about how the suite is invoked and configured, not what a single test file contains. PL1, PL2, PL7, and PL8 are covered by --config-audit (python -O/PYTHONOPTIMIZE strips every assert, warnings not promoted to errors, no coverage gate, addopts that stops the run early), read from the pytest config it parses. The rest need execution or pipeline inspection: PL4 (a collection error counted as "0 tests" while CI stays green), and PL3, PL5, PL6 (a coverage pragma in production code, importorskip hiding a broken import, CI running a subset via -k / -m). They are documented, not promised, and sit outside the "test file" target.

Semantic Family E or F7 (mutation testing and the skill). Mocking the unit under test, asserting the value you fed the mock, re-implementing the production formula, borrowing state from another test, an expected value that contradicts the spec: none of these can be proven by structure. C14 (a snapshot generated from the code's own output) is the only codable corner of this family. The honest path for the rest is mutation testing (mutmut, cosmic-ray), which mutates the production code and checks whether any test goes red, plus the LLM semantic pass in falsegreen-skill.

How the scanner detects. It parses each test file with Python's ast module and inspects the tree. It never imports or runs the test, so a malicious or broken test cannot execute through it. Detection is structural: an assert whose expression is a constant, both sides of a comparison AST-identical, a pytest.raises argument of Exception, a mock-named receiver with a no-parentheses assert_called_once, a Test* class with __init__, and so on. Precision is the priority for HIGH codes, because they block commits: each one is stress-tested against look-alikes (optional-dependency skips, abstract base test classes, @patch-injected mocks, exact-count len(x) == N) and stays quiet on them.

How the semantic pass detects. Cases 10, 11, 12, 15, and 18 cannot be proven by structure. A parser sees a mock but cannot tell whether it replaced an edge (network, disk, clock) or the thing under test. It sees an arithmetic expression but cannot tell whether the expected value was derived independently or copied from the code. That judgment requires reading the production code against an independent oracle - that is what falsegreen-skill does.

Why two confidence levels. A blocking gate that cries wolf gets disabled. So only near-certain, mechanically unambiguous patterns are HIGH (they block). The rest are LOW (they warn) and are starting points for human or semantic judgment, not verdicts.

How falsegreen is validated

A tool that flags tests for not protecting anything has to show it protects something itself.

• The scanner (deterministic). Every rule ships with two tests: one proving it fires on the bad pattern, one proving it stays quiet on a legitimate look-alike. The scanner also runs on its own source on every commit (the self-scan), because the false-positive detector is not allowed to contain one. It is also validated against real-world Python projects - the most recent corpus run covered 40 projects with over 58,000 test functions. That pass surfaced false positives in two rule classes (C7 on deliberate __eq__ tests, C4 on test-named route handlers). Both were fixed, each with regression tests. The HIGH count across all 40 projects after fixes: 0. Each false positive is recorded in the commit history and the CHANGELOG.
• The semantic pass (LLM). Validation for the LLM-based semantic layer is tracked in falsegreen-skill, where benchmark corpora for Python and TypeScript are maintained with precision/recall measurements.

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Test levels (the pyramid)

falsegreen scans tests at every level of the pyramid. Discovery is level-agnostic - it reads any pytest/unittest file - but a few codes are read in light of the level, so a valid pattern at one level is not flagged at another.

• Unit: a function with its boundaries doubled. The oracle is assert (or self.assert*).
• Integration (API and database): API tests through requests/httpx or a framework TestClient (FastAPI, Flask, Django), database tests against a real datastore (SQLAlchemy, the Django ORM, testcontainers). These cross the I/O boundary on purpose, so the response or row IS the verification at that level. The weak-check code (C6) relaxes in the web layer, where the presence of a response is a real check.
• E2E: Playwright for Python and Selenium. expect(locator).to_be_visible() is the oracle.

A real API or database hit inside a test that claims to be a unit test is itself the smell (mystery guest, resource optimism, state leak), not the level of the test. C23 (real file at a literal path), C29 (os.environ mutated), and C30 (mock interceptor never activated) flag those forms.

Diagnostic and coupling codes (opt-in)

Seven additional codes surface smells that do not create false positives but hurt observability and maintainability. All are off by default. Enable with severity = { CODE = "info" } in config. info findings appear in separate DIAGNOSTIC and COUPLING sections and do not affect the exit code.

Code	Smell	What it flags
C22	Async Liar	async def test_* that asserts but never awaits the unit
D1	Assertion Roulette	2+ assertions in one test, all without a msg argument
D3	Duplicate Assert	the same assertion written twice in the same test body
D4	Unnamed Parametrize	@pytest.mark.parametrize with 3+ cases and no ids=
D5	Inline Setup Excess	too many setup statements before the first assert (threshold configurable)
D6	Debug Print	print() call in test body
M2	Long Test Method	test body exceeds long_test_threshold lines (default 50)

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The two layers

Layer	What it is	When it runs	Catches
Scanner (this repo)	Zero-dependency AST analysis	CLI, CI, pre-commit	47 active false-positive codes + 6 opt-in diagnostic and coupling codes
Semantic pass (falsegreen-skill)	LLM-based analysis, Python and other languages	on demand	bug-freezing patterns no static tool can see (cases 10/11/12/15/18)

The scanner is the fast, deterministic pre-filter. For TypeScript, JavaScript, Java, and other languages, use falsegreen-skill.

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What we don't flag (and why)

Measured against the Open Catalog of Test Smells (517 documented smells), only the false-green slice is in scope. These stay out, on purpose:

• Brittleness / false-red (a test that breaks without a real bug): sensitive equality, brittle or fragile assertions. The opposite axis; flagging it would punish correct code.
• Hygiene / maintainability: assertion roulette, magic numbers, long or verbose tests. Linter territory (ruff), and a few are surfaced here as opt-in diagnostics (D1, M2).
• Slow, design, naming, duplication, runtime/culture: none are about whether the test protects.

The boundary is deliberate. Where a smell has a statically provable false-green form, that form is a code here: uncontrolled time or randomness is C16, a hard-coded path is C23, shared module state is C24, an assertion that may never run is C21. See CREDITS.md for the full cross-walk against the literature.

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Install and use

1. CLI (pip)

pip install falsegreen

No permanent install needed: uvx falsegreen tests/ or pipx run falsegreen tests/ runs the latest release from PyPI without touching your environment.

falsegreen                        # scan the current directory
falsegreen tests/                 # scan a folder or a single file
falsegreen --staged               # only the test files staged in git
falsegreen --format sarif         # text (default) | json | sarif | junit
falsegreen --summary              # one-line "N scanned, M flagged" to stderr
falsegreen --output report.sarif  # write to a file
falsegreen --output .falsegreen/  # write report.<ext> into a directory
falsegreen --config-audit         # audit pytest/coverage config (project-layer PL codes)
falsegreen --disable C6,C2b       # turn specific codes off

--config-audit is a separate mode: instead of scanning test files, it reads the project's pytest and coverage config (pyproject.toml, pytest.ini, tox.ini, setup.cfg) and reports the project-layer ways a suite stays green by configuration: PL1 (python -O / PYTHONOPTIMIZE strips every assert at runtime), PL2 (filterwarnings does not promote warnings to errors), PL7 (no coverage gate), PL8 (addopts stops the run early with -x/--maxfail). These complement the per-file scan, which cannot see config.

Each finding is reported with its pyramid level (unit / integration / e2e, read from the file's imports) and a one-line fix hint, and the text summary breaks the findings down by level and lists the most common fixes. --output takes a file or a directory: an extension-less or trailing-slash path (e.g. .falsegreen/) receives report.<ext> for the chosen format. Reports are run artifacts; keep the output directory gitignored.

--format sarif emits SARIF 2.1.0 (HIGH → error, LOW → warning) for GitHub code scanning and PR annotations. --format junit emits JUnit XML for CI dashboards.

python -m falsegreen ... is equivalent. Exit codes: 0 clean, 10 low-confidence findings only, 20 at least one high-confidence finding. No third-party runtime dependencies; Python 3.8+.

2. Pre-commit hook

Add to .pre-commit-config.yaml:

  - repo: https://github.com/vinicq/falsegreen
    rev: v0.6.0
    hooks:
      - id: falsegreen

Then pre-commit install. On each commit it scans the staged test files. HIGH findings block the commit. Bypass once with git commit --no-verify, or set FALSEGREEN_BLOCK=0 to make the hook warn-only.

Keeping the hook current

• Bump the pinned rev. rev is pinned to a tag (v0.6.0 above), so the hook never changes under you. Run pre-commit autoupdate to rewrite it to the latest release, then commit the updated .pre-commit-config.yaml. Pin a tag, never a branch, so local runs and CI use the same scanner.
• --staged and pass_filenames. The hook entry is falsegreen --staged and .pre-commit-hooks.yaml sets pass_filenames: false. The hook reads the staged test files itself from git, so it does not need pre-commit to append the matched file list. Leaving pass_filenames at its default (true) would append every matched path on top of --staged, scanning some files twice. Do not re-enable it or add file arguments in your config; let --staged own the file selection.
• stages override. The hook runs at the pre-commit stage by default. To run it on push instead, set stages: [pre-push] under the hook in your config. A heavier suite can keep the fast HIGH gate at commit time and a fuller pass at push time.

Raw git hook (without the pre-commit framework):

python -m falsegreen.hook_install --repo .      # install
python -m falsegreen.hook_install --uninstall   # remove

3. Semantic pass (multi-language)

For cases that require reading production intent (mocking the unit under test, copying expected from current output, re-implementing the formula), use falsegreen-skill. It covers Python, TypeScript, JavaScript, Java, and other languages.

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Configuration

• Inline suppression: # falsegreen: ignore silences all codes on a line; # falsegreen: ignore[C8] silences one.
• Disable codes globally: --disable C6,C2b.
• Environment: FALSEGREEN_BLOCK=0 makes the pre-commit hook warn instead of block.

Project config file

[tool.falsegreen] in pyproject.toml, or a flat .falsegreen.toml at the repo root (.falsegreen.toml wins if both exist):

[tool.falsegreen]
disable = ["C13b"]            # turn these codes off everywhere
exclude = ["tests/legacy/*"]  # skip files matching these globs
long_test_threshold = 30      # line-count limit for M2 (default: 50)
inline_setup_threshold = 3    # stmt limit for D5 (default: 5)

[tool.falsegreen.severity]
C8 = "high"    # promote: now blocks the commit (exit 20)
C6 = "off"     # same as adding C6 to disable
C22 = "low"    # enable: async-never-awaits check
D1 = "info"    # enable Assertion Roulette
D3 = "info"    # enable Duplicate Assert
D4 = "info"    # enable Unnamed Parametrize
D5 = "info"    # enable Inline Setup Excess
D6 = "info"    # enable Debug Print
M2 = "info"    # enable Long Test Method

severity values: high, low, info, or off. info findings appear in DIAGNOSTIC/COUPLING sections and do not affect the exit code. long_test_threshold and inline_setup_threshold are top-level keys in [tool.falsegreen], not inside [severity]. Precedence, highest first: --disable CLI, inline # falsegreen: ignore, config file, built-in default. Point at a specific file with --config PATH.

Baseline (adopt on a legacy repo)

Record the findings you already have, then fail only on new ones:

falsegreen --write-baseline tests/   # writes .falsegreen-baseline.json, exits 0
falsegreen --baseline tests/         # suppresses recorded findings, fails on new

A finding is fingerprinted by relative path, code, detail, and normalized source line - not line number, so prepending code does not re-trigger a baselined finding. Commit .falsegreen-baseline.json and the ratchet only tightens.

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How it compares

• ruff / flake8-pytest-style - mature, fast lint rules. Overlaps on broad raises (PT011) and assert-in-except (PT017). Run both: falsegreen adds uncollected tests, always-true asserts, self-comparison, mock typos, duplicate parametrize cases, and more.
• PyNose / pytest-smell - test-smell catalogs from research. Broader taxonomy, but no commit gate and no oracle-correctness check.
• mutmut / cosmic-ray - mutation testing, the most honest measure of whether a green suite fails when the code is wrong. Complementary and heavier. falsegreen is the cheap pre-filter you run on every commit; mutation testing is the deep audit you run on suites that matter.
• falsegreen-skill - the LLM companion for the semantic pass and for TypeScript, JavaScript, Java, and other languages.

The defensible gap: a deterministic commit gate that catches the mechanical false-positive patterns with zero runtime dependencies, paired with an LLM semantic layer that catches the oracle-correctness cases no static tool can see.

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Project layout

falsegreen/
  src/falsegreen/scanner.py        the deterministic scanner
  src/falsegreen/hook_install.py   raw git-hook installer
  docs/guide.md                    plain-language guide to every case
  examples/python/                 a BAD + CLEAN sample for every detected code
  tests/test_scanner.py            the scanner's own tests
  .pre-commit-hooks.yaml           pre-commit integration
  pyproject.toml                   packaging

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Contributing, security, license

• CONTRIBUTING.md - dev setup, how to add a detection rule, the false-positive policy, Conventional Commits.
• SECURITY.md - how to report a vulnerability privately.
• CODE_OF_CONDUCT.md - Contributor Covenant 2.1.
• CREDITS.md - research falsegreen builds on (Soares rotten-green work, PyNose, test-smell catalog, agentic-LLM studies), with author credit.
• License: MIT, see LICENSE.

Contributors ✨

Thanks to the people who keep false-green tests out of real suites (emoji key):

Vinicius Queiroz 💻 📖 🤔 🚧 🚇 ⚠️ 🔬

Home Seller 💻 📖 🚇 ⚠️

New contributors are added automatically; the table also recognizes non-code work (docs, ideas, infrastructure, tests, research) via the all-contributors spec.