Gate code changes by structural complexity impact

impact-gate

A merge gate that flags changes piling complexity onto code that is already complex,
before a class quietly grows into a god class nobody can safely touch. Run it as a
standalone CLI, a git pre-commit hook, or a plugin in GitHub, GitLab, and Jenkins CI.

Website: https://impactgate.officefloor.net

The pattern it catches is gradual. A class gains one more method, then another, then
another. Each change looks reasonable on its own. But over dozens of them the class ends
up doing five different jobs, and every edit gets riskier. That slow accretion is what we
call structural decay (also considered cohesive erosion). The gate scores each change against a base (main by default), so
it shows up while it is still cheap to fix:

impact = files_changed * Σ max(WMC_other, 1) * CC * Δlines      (over changed functions)

WMC_other is the complexity that was already in the file or class you are editing,
measured before your change. Adding a brand new file is cheap. There was nothing there to
make worse. Adding a complex method to an already heavy class is expensive. The gate
measures that difference, not the raw size of the diff.

For the reasoning behind the formula, see Measuring the Blast Radius of
Change on
the OfficeFloor blog.

When impact is too high, the gate asks you to simplify the change or refactor the code
it touches. It can warn (report only) or block (fail the build).

Languages

The gate is language agnostic. It scores changes in any of these languages:

Java, C#, C, C++, JavaScript, TypeScript, Python, Go, Kotlin, Swift, Ruby, PHP, Rust,
Scala, Objective-C, Lua, and TTCN-3.

Complexity is parsed per function by lizard. A
mixed language repo is scored the same way throughout.

You can add or remap extensions in the measure config (lang_by_ext).

The grading curve is calibrated per language for Python, Java, TypeScript, C#,
JavaScript, C, Scala, and Go. These come from the seed corpus. The other languages are
still measured and graded. They fall back to a pooled cross language distribution that
holds until your project baseline builds up its own history.

Install

pip install impact-gate         # installs the `impact-gate` command

Or run it without installing anything, via the published image (git is bundled;
mount the repo to score at /repo):

docker run --rm -v "$PWD:/repo" ghcr.io/officefloor/impact-gate \
  score --mode range --base origin/main

To hack on it locally, install from a checkout instead:

python -m venv .venv && . .venv/bin/activate
pip install -e '.[dev]'         # editable install plus the test deps

Use

# The commit you are about to make (pre-commit): staged vs HEAD. This is the default.
impact-gate score

# Uncommitted local edits: working tree vs HEAD.
impact-gate score --mode worktree

# CI or PR review: the committed branch vs main (merge-base..HEAD).
impact-gate score --mode range --base origin/main --format json

# Set thresholds and enforcement. You can also put these in .impact-gate.yml.
impact-gate score --warn-at 50000 --block-at 200000 --enforcement block

Exit codes. 0 means ok or warn (the change is allowed). 2 means blocked (impact too
high under --enforcement block). 1 means a usage or environment error.

Every report also lists the files to consider for refactoring, ranked by their share
of the impact. The change level number gates; the per file ranking points at where the
decay is concentrating, so a file quietly growing into a god class surfaces as a
candidate before it blocks anything.

A source file whose diff is larger than max_diff_lines (200,000 by default, in the
measure config) is almost always a generated dump or a vendored blob. The gate skips it
so it neither distorts the number nor slows scoring, and lists it under skipped so
the result is never silently wrong.

Use as a git pre-commit hook

Gate every commit locally, before CI:

# Installs .git/hooks/pre-commit. It scores the staged change on each commit.
impact-gate install-hook

With enforcement: block in .impact-gate.yml, a commit whose impact is too high is
blocked; on warn (or off) the report prints and the commit proceeds. Re-run with
--force to overwrite an existing pre-commit hook.

Prefer the pre-commit framework? This repo ships a hook
definition - add to your .pre-commit-config.yaml:

repos:
  - repo: https://github.com/officefloor/ImpactGate
    rev: v0.3.0
    hooks:
      - id: impact-gate

Grade against a distribution (the curve)

A raw threshold is hard to set: a typical change's impact varies by orders of magnitude
across languages and projects. Instead of guessing a number, grade a change by its
percentile against a distribution, and gate on the percentile.

# Build (or refresh) the project's own impact distribution from the merged history.
# Writes .impact-gate-baseline.json. Re-run it as the branch moves.
impact-gate baseline --base-ref main

# Gate on the grade instead of an absolute number.
impact-gate score --curve --warn-percentile 90 --block-percentile 98

The grade blends two distributions:

• a seed prior shipped with the tool - per language percentile tables built from a
  20 repo open source corpus, with a pooled fallback for languages not in the table;
• the project baseline - the repo's own per change distribution, walked from the
  merged mainline (only landed work; in flight branches are never reached).

The blend weights the project by w = n / (n + K), where n is the number of landed
changes behind the baseline and K (curve_prior_weight, default 200) is how much
history it takes to trust the project over the seed. A fresh repo with no baseline file
grades on the seed alone; a deep history leans on itself. The grade shows in every
format next to the raw number.

Configure with .impact-gate.yml (repo root)

warn_at: 50000          # impact above which to warn
block_at: 200000        # impact above which to block
enforcement: warn       # off, warn, or block. Start on warn. Flip to block when ready.
tolerance: 1.0          # CI-adjustable multiplier on both thresholds. Above 1 is more lenient.
# measure_config: .impact-measure.yml   # optional: ignore globs and language overrides

# Grading curve (percentile gate). When enabled, warn_at/block_at are ignored and the
# gate uses the percentiles below instead.
curve_enabled: false           # gate on the percentile grade instead of absolute numbers
warn_percentile: 90            # grade at or above this warns
block_percentile: 98           # grade at or above this blocks
curve_prior_weight: 200        # K in w = n/(n+K): history needed to trust the project over the seed
baseline_file: .impact-gate-baseline.json   # where `impact-gate baseline` caches the distribution

CLI flags override the file. A CI job can pass --tolerance or --warn-at. So a team
can dial tolerance without editing the repo. The curve knobs have flags too: --curve,
--warn-percentile, --block-percentile, --baseline-file.

Use in GitHub Actions

Add a workflow to your repo. The action scores the PR branch against its base and writes
a summary. fetch-depth: 0 is required so the base branch and merge base are present.

name: Change impact
on: pull_request
permissions:
  contents: read
  pull-requests: write         # so the action can post the score as a PR comment
jobs:
  impact:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v5
        with:
          fetch-depth: 0
      - uses: officefloor/ImpactGate@v0
        with:
          enforcement: warn        # switch to block when ready
          # warn-at: 50000
          # block-at: 200000
          # tolerance: 1.0

The score appears in the job summary and as a sticky comment on the PR (one comment,
updated each run). In block mode the job fails when impact exceeds the block threshold.
Make the check required in branch protection to gate merges. The comment needs
pull-requests: write. Without it the run still passes and just skips the comment.

Use in GitLab CI

A ready-made job is in ci/gitlab-ci.yml. Copy it into your
.gitlab-ci.yml, or include it remotely:

include:
  - remote: 'https://raw.githubusercontent.com/officefloor/ImpactGate/v0/ci/gitlab-ci.yml'

It runs on merge request pipelines, scores the MR against its base
($CI_MERGE_REQUEST_DIFF_BASE_SHA) with the published Docker image, and - when a CI/CD
variable GITLAB_TOKEN with the api scope is set - posts a sticky note to the MR (one
note, updated each run). Without the token it still scores and gates; it just skips the
note. In block enforcement the job fails when impact is too high; make it required in
the merge request settings to gate merges.

Use in Jenkins

A pipeline snippet is in ci/Jenkinsfile. It runs the Docker image on
an agent with Docker, scoring the change against its target branch
(origin/${CHANGE_TARGET:-main}) and archiving the report. In block enforcement the
stage fails when impact is too high. Posting the score back to the PR/MR is left to your
SCM integration; to post it with the tool itself, run impact-gate comment in the
container with the provider's token and env set.