# Validation Fundamentals: URS That Actually Helps Testing (Not Just Paperwork)

> A User Requirements Specification (URS) should make validation easier. But many URSs become vague wish lists. When requirements are unclear, tests become random, and traceability becomes

- Author: Tomaž Berden (https://lifescienceai.org/authors/tomaz-berden/)
- Published: 2026-06-08
- Category: Fundamentals
- Canonical URL: https://lifescienceai.org/articles/validation-fundamentals-urs-that-helps-testing/
- Word count: 287
- Platforms named: Qualitum (https://qualitum.ai/)

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## Your URS is your testing compass

A User Requirements Specification (URS) should make validation easier. But many URSs become vague wish lists. When requirements are unclear, tests become random, and traceability becomes painful.

## What a strong URS looks like

Specific: “The system shall require electronic signature for batch release approval.”

Verifiable: You can test it in a defined scenario.

Risk-aware: Requirements tied to critical workflows and critical data are clearly marked.

## The 4 fields that improve URS quality overnight

1) Requirement statement. Use “shall” language and keep it singular.

2) Rationale. Why do you need it? Link to process or compliance need.

3) Risk tag. Critical or non-critical. Use a simple label that drives testing depth.

4) Acceptance criteria. One or two bullet-style outcomes that define success.

## Common beginner mistake

Writing requirements that describe how to implement instead of what to achieve. Keep the URS focused on user needs and compliance outcomes. Leave design details to configuration specs.

## Practical exercise

Take your next URS draft and highlight every sentence that cannot be tested. Rewrite those into verifiable statements. Your testing team will thank you, and your traceability matrix will build itself.

## How this looks with an agentic layer

The fundamentals above do not change when validation is automated - they get enforced earlier. On a layer like Qualitum, intended use, risk and evidence are structured inputs rather than documents someone remembers to write: agents draft against them, maintain the traceability, and hand the result to a named human for approval.

- Intended use and critical data are captured once and reused across the lifecycle
- Evidence is generated with its traceability attached, not reconstructed for the audit
- The approval - and the accountability - stays with your named reviewer

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Source: LifeScienceAI - https://lifescienceai.org/articles/validation-fundamentals-urs-that-helps-testing/. Editorial analysis, not regulatory advice. Cite as: Tomaž Berden, "Validation Fundamentals: URS That Actually Helps Testing (Not Just Paperwork)", LifeScienceAI, June 8, 2026.