Rewrite Rate: a pre-registered protocol for measuring how often coding agents make test suites pass by editing the tests

Coding agents sometimes make a failing test suite pass by editing the test rather than the code. Every existing signal for this is a proxy — a test file changed, an assertion count dropped, a skip appeared — and none of them establishes that the change to the test is why the suite went green. Reverting the agent's test edits and re-running the suite does establish it. This document registers, before any data is collected, the method for measuring it. The Rewrite Rate is the share of runs an agent finished green that turn red when its test edits alone are reverted. Fixed here in advance: the task set (33 tasks across 9 public Go repositories, fingerprint blake2b:ee02cf85bdf681de63d60ed0e83429b2), the agents and their pinned versions, the prompt, the counting rule, the stability filter, the exclusion criteria, and what is published regardless of outcome. The tool used to take the measurement is written by the author of this registration. That is a conflict of interest, and stating the method in advance is the only thing that makes the result worth reading. A Rewrite Rate near zero would mean the tool's premise is wrong; that result is published on the same terms as any other. Task set, construction script and analysis: https://github.com/angelnicolasc/Warrant

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-08-14
DOI
https://doi.org/10.5281/zenodo.21926605
Primary Topic
Artificial Intelligence in Games
Type
preprint
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
preprint

Rewrite Rate: a pre-registered protocol for measuring how often coding agents make test suites pass by editing the tests

Nick Corzo Cerutti
Zenodo (CERN European Organization for Nuclear Research)
Artificial Intelligence in Games
preprint

Rewrite Rate: a pre-registered protocol for measuring how often coding agents make test suites pass by editing the tests

Nick Corzo Cerutti
preprint en

Abstract

Coding agents sometimes make a failing test suite pass by editing the test rather than the code. Every existing signal for this is a proxy — a test file changed, an assertion count dropped, a skip appeared — and none of them establishes that the change to the test is why the suite went green. Reverting the agent's test edits and re-running the suite does establish it. This document registers, before any data is collected, the method for measuring it. The Rewrite Rate is the share of runs an agent finished green that turn red when its test edits alone are reverted. Fixed here in advance: the task set (33 tasks across 9 public Go repositories, fingerprint blake2b:ee02cf85bdf681de63d60ed0e83429b2), the agents and their pinned versions, the prompt, the counting rule, the stability filter, the exclusion criteria, and what is published regardless of outcome. The tool used to take the measurement is written by the author of this registration. That is a conflict of interest, and stating the method in advance is the only thing that makes the result worth reading. A Rewrite Rate near zero would mean the tool's premise is wrong; that result is published on the same terms as any other. Task set, construction script and analysis: https://github.com/angelnicolasc/Warrant

Zenodo (CERN European Organization for Nuclear Research)
Reduced inequalities
Artificial Intelligence in Games
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.