QA Intelligence
AI-drafted test cases from acceptance criteria, approved by QA and traced to the requirement.
Learn moreTraceability both ways
Requirement to Code Traceability
Requirement to code. And back.
- Requirement IDs carried into stories and pull requests
- Code read back into journeys a person confirms
- Every finding linked to its source file
How does SyncupHUB trace requirements to code, and back?
SyncupHUB traces delivery in both directions. Forward, a requirement’s ID travels with its acceptance criteria into stories, then into the commits, pull requests, builds and deployments linked to them. Backward, AI Documentation reads an existing repository and recovers its routes, contracts, architecture and candidate business journeys, which a person confirms and links to requirements.
How it works
Start from the requirement
Requests grow into BRDs with numbered requirements, and each acceptance criterion links to a requirement ID.
Carry it into the work
Stories keep the requirement they came from, and commits, pull requests, builds and deployments from GitHub, GitLab or Azure DevOps link back to the story.
Read the code back
AI Documentation analyses the repository: static route, contract and dependency extraction, architecture diagrams and candidate business journeys.
Confirm and close the loop
A person confirms each recovered journey and links findings to remediation stories and architecture decisions, so documented intent and shipped code meet.
What’s included
- Requirement IDs linked to acceptance criteria
- Stories linked to commits, pull requests, builds and deployments
- Requirement-to-test traceability
- Evidence-bound engineering requests, reviewed before they run
- Static route, contract and dependency extraction
- Candidate business journeys a person confirms
- Snapshot and baseline comparison, and change-impact analysis
- Source-linked findings
What it needs
Stated plainly, before a demo does.
- Static analysis does not prove runtime behaviour.
- Engineering requests run only on execution infrastructure you configure.
- Repository and CI connections link the evidence; they do not replace those tools.
Questions about Requirement to Code Traceability
What is requirement-to-code traceability?
It is the ability to follow a requirement to the code that implements it, and back. In SyncupHUB a requirement’s ID travels into its stories, and commits, pull requests, builds and deployments link to those stories, so you can open a requirement and see what shipped for it.
Can SyncupHUB recover requirements from existing code?
Yes, as a starting point a person confirms. AI Documentation analyses the repository, including routes, contracts, dependencies and architecture, and proposes candidate business journeys. Once confirmed, they link to requirements and stories, which is how teams rebuild lost knowledge of a legacy system.
Which code repositories does it work with?
GitHub, GitLab and Azure DevOps. Commits, pull requests, builds and deployments link back to the work item, and SonarQube code-quality signal can sit alongside the delivery and test evidence for a release.
Does repository analysis prove how the code behaves?
No. Static analysis describes what the code says, not what it does at runtime, and SyncupHUB labels its findings that way. Every finding links to the source file it came from, so an engineer can check it.
Related features
Document Spaces
Documents with comments, approvals and version history, kept next to the stories they govern.
Learn moreAI Agents for Every Role
Seventeen persona agents and 59 sub-agents, all reading the same delivery model.
Learn moreSee Requirement to Code Traceability on your own delivery
A 30-minute walkthrough on your delivery model, not a generic demo.