Dependency Management

Dependency Management

Decide what to depend on, keep dependencies current, respond to advisories, and reduce supply chain risk. Stack-agnostic principles; specifics vary by package manager.

When to use

• Setting up dependency hygiene for a new or existing project
• Responding to a security advisory
• Major version upgrade of a key dependency
• Adding a new dependency (evaluation, decision)
• Removing a dependency (cleanup)
• Audit of what's installed and what's actually used
• Setting an update cadence and policy
• Diagnosing a broken build after an update

When NOT to use

• General code review (use code-review-web)
• Vulnerability scanning of infrastructure (use security-baseline)
• Pinning vendor or service contracts (use vendor-evaluation)
• Performance impact of dependencies (use performance-optimization)

Required inputs

• Package manager and lockfile in use (npm, yarn, pnpm, pip, gem, composer, etc.)
• Current dependency list (production and dev)
• Current advisories (run audit; check service like Snyk, Dependabot)
• Update history (when were major dependencies last updated)
• Risk profile (production criticality, change tolerance)

The framework: 4 categories of dependency

Every dependency falls into one of these. The category drives the policy.

Category 1: Critical runtime

Code that runs in production and would break the system if it failed.

Examples: framework, database driver, payment SDK, authentication library.

Policy:

• Update cadence: monthly minor, quarterly major (with planning)
• Security: patch within 24-72 hours of advisory, 24h for critical
• Pinning: exact version pins or narrow ranges
• Vetting: thoroughly evaluated before adoption

Category 2: Supporting runtime

Code that runs in production but is replaceable or non-critical.

Examples: utility libraries, formatting, non-core integrations.

Policy:

• Update cadence: monthly together with critical
• Security: patch within a week of advisory
• Pinning: narrow ranges acceptable (e.g., ^1.2.3)
• Vetting: moderate evaluation; alternatives considered

Category 3: Dev/build

Code that runs only during development or build, not in production.

Examples: bundlers, linters, test frameworks, type checkers.

Policy:

• Update cadence: quarterly
• Security: patch within a week (still matters; supply chain attacks target build tools)
• Pinning: ranges acceptable
• Vetting: lighter; broken dev tools surface fast

Category 4: Optional/dev-only-personal

Tools individual developers use that aren't part of shared dev environment.

Not really managed at the project level. Mentioned for completeness.

The framework: 5 risk dimensions

When evaluating a dependency, consider:

Dimension 1: Maintenance health

• Last commit date (months ago is concerning)
• Open issue count and age
• Number of maintainers
• Sponsorship or commercial backing
• Roadmap visibility

A dependency abandoned a year ago is a liability waiting to surface.

Dimension 2: Surface area

• Size of the package
• Number of transitive dependencies
• Footprint in the bundle (for client-side)
• Privileges required (file system, network, etc.)

A small dependency that pulls in 50 transitive packages has the surface area of all 50.

Dimension 3: Replaceability

• How hard would it be to remove?
• Are there alternatives?
• Could the functionality be implemented in-house?
• Is the API standard or idiomatic?

A dependency you can't replace is leverage you've granted to its maintainer.

Dimension 4: Trust

• Reputation of the maintainer or organization
• Code quality (skim the source)
• License (GPL, MIT, BSD, proprietary, none)
• History of security issues
• Supply chain practices (signed releases, 2FA on publishes)

Dimension 5: Cost

• Time to evaluate, integrate, maintain
• Risk of breaking changes
• Lockfile entropy
• Potential security exposure
• Bundle size impact (for client-side)

Every dependency has a cost. Free packages aren't free.

Workflow

Step 1: Inventory

Run a dependency listing:

# npm/yarn/pnpm
npm ls --all --json

# pip
pip list

# gem  
bundle list

For each top-level dependency, categorize (critical / supporting / dev). For transitives, you generally don't manage individually unless one becomes a problem.

Step 2: Audit

Run the security audit:

npm audit
yarn npm audit  # Yarn 2+; "yarn audit" on Yarn 1 Classic
pip-audit
bundle audit

For each finding:

• Severity (critical, high, medium, low)
• Package and version
• Fix available?
• Used directly or transitively?

Step 3: Categorize and prioritize

Critical and high in production code are emergencies. Low and medium are scheduled work.

Step 4: Test before merging fixes

Even patch-level updates can break things. For critical dependencies:

• Run the full test suite
• Smoke-test in staging
• Watch the monitoring after rollout

For supporting and dev:

• Run the test suite
• A failed test is OK to investigate; don't merge a known-broken update

Step 5: Plan major version upgrades

Major versions break things. Plan rather than rush.

For each major upgrade:

• Read the changelog and migration guide
• Estimate the migration effort
• Schedule the work (don't do it under deadline pressure)
• Branch and test thoroughly
• Plan a staged rollout if it's a critical dependency

Don't sit on major versions indefinitely. The longer you wait, the more painful the upgrade.

Step 6: Set the policy

Document:

• Update cadence (e.g., monthly review, quarterly upgrades)
• Security response SLA (e.g., critical within 24h)
• Approval for new dependencies (who signs off)
• Removal criteria (when do we drop a dependency)
• Pinning strategy (exact, narrow range, broad range)

The policy is what survives team turnover. Without it, dependency management becomes chaotic ad hoc work.