Question
How effectively can an automated tool identify quantum-vulnerable cryptographic components and support post-quantum migration planning in small software systems?
Research
The method behind Q-Migrate.
Q-Migrate studies how traceable cryptographic evidence can support initial migration planning, with cloud and distributed systems providing the wider context.
Method
A design-science study using versioned rules, traceable findings and controlled evaluation. Diagnostic probes also test whether the score gives a misleading impression.
Evidence
The Python prototype passes 49 tests and recovers 39 expected finding identities across four co-designed fixtures. Performance on unseen repositories and benefits to users’ planning decisions remain unverified.
Cloud and distributed systems
From a finding to a service decision.
The dissertation considers how findings could inform reviews of ownership, dependencies, data lifetime and staged change. Provider and runtime evidence would need to be collected separately. Cloud integration remains future work.
The score is experimental: critical findings can sit alongside a reassuring total, and excluded evidence can be missing from coverage. The browser companion demonstrates the workflow; its analysis has not been shown equivalent to the evaluated Python prototype.
Dissertation in progress
Design and Evaluation of Q-Migrate
The final PDF and Word versions will be available here once the dissertation is complete.