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Legal & ComplianceGenerated accuracy model review: 2026-05-06

Severance Weeks Calculator accuracy and testing

This page documents how Calwarden builds trust for this calculator: source notes, regression-style default tests, limitations, assumptions, unit handling, rounding, and visible change history.

Formula source

  • Estimated severance weeks = years of service x weeks per service year, raised to the minimum weeks if entered, then limited by cap weeks if entered.

Test cases

Default input regression check

Generated from the checked-in default inputs and calculate function.

Inputs

  • Years of Service: 6 years
  • Weeks per Service Year: 2 weeks/year
  • Minimum Weeks: 0 weeks
  • Cap Weeks: 26 weeks

Expected outputs

  • Estimated Severance Weeks: 12 weeks

Known limitations

  • This tool does not evaluate release agreements, WARN notices, benefit continuation, offsets, tax treatment, eligibility, or enforceability.

Assumptions

  • Years of service are entered by the user and may include credited partial years if the policy allows.
  • A cap or minimum of 0 means that limit is ignored.
  • Defaults are editable examples and are not jurisdiction-specific legal rules.
  • All calculation inputs are processed locally in the browser for privacy.

Unit handling

  • Years of Service accepts values in years.
  • Weeks per Service Year accepts values in weeks/year.
  • Minimum Weeks accepts values in weeks.
  • Cap Weeks accepts values in weeks.
  • Estimated Severance Weeks is displayed in weeks.

Rounding rules

  • Number displays use up to 2 decimal places in the calculator UI.
  • Input precision follows configured step values where provided.

Version history

1.0.0 - 2026-05-06

Generated accuracy and testing page from the current severance-weeks-calculator calculator definition.

Change log

2026-05-06

Published default regression test documentation and metadata fallbacks for Severance Weeks Calculator.

Calculator transparency

Accuracy pages are generated from checked-in calculator definitions and can be upgraded with curated review metadata over time.

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