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A free scan shows the junk files, broken settings and background clutter dragging Windows down - then fixes them in one click.Free scan · Windows 10 & 11In a 2026 study of 181 changes across 17 open-source projects, most judged changes had at least one test that failed when the changed source code was reverted. That is evidence the test noticed the change—not proof that the fix was correct or that the result applies to all software projects.
What the 181-change study measured
Receipts, an open-source tool, runs tests associated with a code change twice: first with the change applied, then after reverting the changed source files to their parent-commit or pull-request merge-base versions. The tests, dependencies, and configuration stay at their newer versions in both runs. The question is whether a test that passes with the change fails against the older source.
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The study, published by syntaxixr in 2026, covered two samples: 81 maintainer fix commits drawn from 12 libraries, and 100 agent-fingerprinted pull requests drawn from five agent-heavy repositories. Maintainer commits were selected from recent qualifying changes, up to eight per repository; the agent sample included up to 20 of the newest qualifying PRs per repository. Agent PRs could be open or closed, and some were unmerged.
The Tool Desk
Outbyte Driver Updater FREEFix the driver behind crashes, sound loss and screen glitchesFind Drivers →Outbyte PC Repair FREEClear out junk files and repair common Windows errorsFree Scan →This is a counterfactual check of test sensitivity. It asks whether a test reacts to the source change, not whether the change fixes the underlying bug, covers every relevant behavior, or is safe to ship. The study describes its samples as small and non-random, so the results should not be read as ecosystem-wide rates. Study methods and results · Receipts project documentation
What the study found
Ten maintainer changes and nine agent PRs could not be judged for environmental reasons. The percentages below use only the remaining judged changes.
| Sample | Judged | Proven | Weak-only |
|---|---|---|---|
| Maintainer fix commits | 71 of 81 | 64 of 71 (90%) | |
| Agent-fingerprinted pull requests | 91 of 100 | 75 of 91 (82%) | 9 of 91 (10%) |
“Proven” means at least one test failed against the old source, with no weak or theater result. The figures show that many changes in both samples had tests sensitive to the source change. They do not establish that maintainer-authored tests are generally better than agent-authored tests: the repositories and selection methods differ, PRs included unmerged work, and agent attribution relied on fingerprints rather than verified authorship.
The agent sample included 87 PRs with Claude Code fingerprints, six with Codex fingerprints, six with Cursor fingerprints, and one with a Copilot fingerprint. Those counts describe detected fingerprints in this sample, not exclusive authorship; the study notes that people may have steered the work.
Why a failing test can still be weak evidence
Nine of the 91 judged agent PRs were classified as weak-only. In the described pattern, a test module imports a name introduced by the change at the module’s top level. When the changed source is reverted, that name no longer exists, so the test module fails to load. The failure looks like a test noticing the change, but the test never reaches the old behavior it was meant to check.
A practical mitigation is to import the new name inside only the tests that need it, rather than at module load time. That lets the test module load against the old source, making it possible to distinguish a genuine behavioral failure from a missing import. The study discusses this pattern in an example from a Claude Agent SDK Python PR. The article’s example and explanation
Receipts uses several verdicts to distinguish outcomes:
Rank #4
- PROVEN: A test fails without the change.
- GUARD: A test passes on both sides but sits alongside a test that proves the change.
- THEATER: Tests pass with and without the change, and none proves it.
- WEAK: A test fails against old source because code it calls did not exist yet, rather than because it detects changed behavior.
- BROKEN, FLAKY, and SKIPPED: Other outcomes the study tracks, including tests that cannot yield a reliable pass/fail comparison.
At the change level, the study calls a change “mixed” when some tests prove it while others are weak; “unproven” when every test passes without the change; and “weak only” when the tests fail against old source solely because the called code is new.
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Why some changes are hard to prove with a test run
The study says theater was uncommon in its samples, but gives examples that show why a green or unchanged result can be ambiguous: a type-only change may not affect runtime tests; a Windows-specific newline fix may not be exercised on Linux; a dateutil representation fix may produce output that already matches inherited behavior; or a maintenance commit may mention an issue without changing behavior that the selected tests can demonstrate. A test verdict depends on both the nature of the change and the environment where it runs.
Best Value
How to use this idea on your own changes
A normal green test run tells you that the tests passed with your code. A revert comparison asks a different question: would those same tests fail if the source change were absent? That can expose tests that pass but do not detect the change, while import-time failures can reveal cases where an apparent failure is not behavioral evidence.
Receipts’ README describes a CLI, a GitHub Action, and an agent skill, and lists support for pytest, vitest, and jest. It states that the tool is deterministic, needs no LLM or API keys, and runs a project’s own test runner. The documented baseline is Node 20+ and Git. The Action can report on pull requests and fail checks for configured verdicts; its example recommends the pull_request event and checkout credentials that do not persist. A report comment requires comment permission. These are capabilities described by the project, not independently verified results. Receipts README
The study also provides reproduction commands, raw repository results, and a Hugging Face dataset. Those materials are the project’s supplied route to inspect or reproduce its analysis; the complete study was not independently rerun here. Study reproduction information
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