Hotspots

Website: https://hotspots.dev  |  Docs: https://docs.hotspots.dev  |  Crates.io:

Install: brew install Stephen-Collins-tech/tap/hotspots  |  npm install -g @stephencollinstech/hotspots  |  pip install hotspots-cli  |  cargo install hotspots-cli

Find the code that's actually causing problems.

Your codebase has thousands of functions. Some are messy but never break. Others are complex AND change constantly — those are your hotspots, the 20% of code causing 80% of your bugs, incidents, and slowdowns.

Install

brew install Stephen-Collins-tech/tap/hotspots   # macOS
npm install -g @stephencollinstech/hotspots       # any platform
pip install hotspots-cli                          # any platform
cargo install hotspots-cli                        # Rust toolchain
curl -fsSL https://raw.githubusercontent.com/Stephen-Collins-tech/hotspots/main/install.sh | sh  # Linux

Windows: download the binary from GitHub Releases.

Verify: hotspots --version

GitHub Action:

- uses: Stephen-Collins-tech/hotspots/action@v1
  with:
    github-token: ${{ secrets.GITHUB_TOKEN }}

Quick Start

# Find your hotspots
hotspots analyze src/

# Critical (LRS ≥ 9.0):
# processPlanUpgrade    src/api/billing.ts:142    LRS 12.4  CC 15  ND 4  FO 8  NS 3
#
# High (6.0 ≤ LRS < 9.0):
# validateSession       src/auth/session.ts:67    LRS 9.8   CC 11  ND 3  FO 7  NS 2

Critical = refactor now. High = refactor next time you touch it. Moderate = block increases. Low = leave it alone.

Common commands

# Per-function explanations with refactoring advice
hotspots analyze . --mode snapshot --format text --explain --top 10

# Block complexity regressions in CI
hotspots analyze src/ --mode delta --policy

# Compare any two git refs
hotspots diff main HEAD --top 10 --policy

# Interactive HTML report
hotspots analyze src/ --mode snapshot --format html

# JSON for tooling/AI
hotspots analyze src/ --format json

# Track trends over time
hotspots trends .

# Train a repo-specific ranker from your bug history
hotspots train . --blame --eval

How It Works

Hotspots computes a Local Risk Score (LRS) per function from four structural metrics:

LRS = 1.0×R_cc + 0.8×R_nd + 0.6×R_fo + 0.7×R_ns

where each component is log-scaled and capped to prevent outliers from dominating (full formula, caps, and weight rationale).

In snapshot mode, LRS is combined with git history (churn, touch frequency, recency) and call graph metrics (fan-in, PageRank, SCC membership) to compute an Activity Risk Score and place each function in a triage quadrant:

Risk bands: Low (< 3) · Moderate (3–6) · High (6–9) · Critical (≥ 9)

Supported Languages

TypeScript · JavaScript · Go · Python · Rust · Java · C/C headers · C# · Vue · Astro

All 13 file extensions (.ts, .tsx, .mts, .cts, .js, .jsx, .mjs, .cjs, .go, .py, .rs, .java, .c, .h, .cs, .vue, .astro) work out of the box.

CI/CD Integration

GitHub Action (zero config)

name: Hotspots
on: [pull_request, push]
jobs:
  analyze:
    runs-on: ubuntu-latest
    permissions:
      contents: read
      pull-requests: write
    steps:
      - uses: actions/checkout@v4
        with:
          fetch-depth: 0
      - uses: Stephen-Collins-tech/hotspots-action@v1
        with:
          github-token: ${{ secrets.GITHUB_TOKEN }}

Posts PR comments, generates HTML reports, fails builds on policy violations.

Manual CI

# Fail CI if new critical functions introduced or LRS increases ≥ 1.0
hotspots analyze src/ --mode delta --policy

Exit code 1 on blocking violations, 0 on warnings only.

Key Features

Policy engine — blocks: new critical-risk functions, LRS regressions ≥ 1.0, net repo regression ≥ 5.0. Warns: approaching thresholds, rapid growth > 50%.

Driver labels — each function gets a primary diagnosis: high_complexity, deep_nesting, exit_heavy, high_churn_low_cc, high_fanout_churning, high_fanin_complex, cyclic_dep, or composite.

Pattern detection — 13 named patterns in two tiers: structural (always, e.g. complex_branching, god_function) and enriched (snapshot mode, e.g. churn_magnet, cyclic_hub, volatile_god).

Suppression comments — exclude functions from CI failures while keeping them visible:

// hotspots-ignore: legacy payment processor, rewrite scheduled Q2 2026
function legacyBillingLogic() { ... }

Trained ranker — fit a RandomForest from your repo's bug-fix history:

hotspots train . --blame --eval   # train + check P@K vs base rate

Output formats — text (terminal), json (machine), jsonl (streaming), html (interactive), sarif (GitHub Code Scanning).

Configuration — .hotspotsrc.json in project root (auto-discovered):

{
  "include": ["src/**/*.ts"],
  "exclude": ["**/*.test.ts"],
  "thresholds": { "moderate": 3.0, "high": 6.0, "critical": 9.0 },
  "weights": { "cc": 1.0, "nd": 0.8, "fo": 0.6, "ns": 0.7 }
}

Documentation

• docs/USAGE.md — workflows, CI setup, output formats, policy engine, suppression, training, snapshot management
• docs/REFERENCE.md — complete CLI reference, all flags, config options, JSON schema, metrics formula
• docs/ARCHITECTURE.md — system design, analysis pipeline, invariants, design decisions
• docs/CONTRIBUTING.md — dev setup, adding languages, release process

Why Hotspots?

vs ESLint complexity rules — ESLint checks one metric in isolation with no git context. Hotspots combines four metrics, git history, and call graph topology into a single prioritized list.

vs SonarQube / CodeClimate — Enterprise platforms requiring server infrastructure. Hotspots is a single binary, zero config, works offline, results in seconds.

vs code reviews — Reviews catch complexity subjectively and miss gradual drift. Hotspots enforces objective thresholds automatically on every commit.

Contributing

• Bug reports: GitHub Issues
• Feature requests: GitHub Discussions
• PRs: see docs/CONTRIBUTING.md

License

MIT — see LICENSE-MIT.