Resources: practices

Netspective Unified Process | Agile Quality System for Regulated SDLC

An agile quality system and SDLC for regulated IT deliverables. Meet FDA, HIPAA, NIST, and FedRAMP requirements with audit-ready documentation.

What Regulated QA Actually Requires

What separates regulated QA from general software QA: a documented quality system, risk-based classification, independently evidenced verification and validation, and an auditable traceability chain — not just more test cases.

Verification vs. Validation in High-Consequence Systems

Verification vs. validation in regulated software: verification proves you built the thing right (design output meets design input); validation proves you built the right thing (meets user needs and intended use). A worked decision table.

Regulated Release-Readiness Assessment Protocol

A regulated software release-readiness protocol: a scored go/no-go assessment covering verification completeness, validation completeness, risk-control verification, and closed traceability — not just a passing test suite.

Medical Device Legacy Software Modernization & Remediating SOUP

Modernizing legacy medical device software: SOUP evaluation under IEC 62304 Clause 8.1.2, a remediation triage process, and how to scope architectural boundaries so a component swap doesn't re-trigger full-system re-verification.

HIPAA Engineering Practices Beyond the BAA Checklist

HIPAA Security Rule technical safeguards (45 CFR §164.312) beyond the Business Associate Agreement: access control, append-only audit control, integrity, authentication, and transmission security — with a worked checklist.

Audit-Ready SDLC for Digital Health Platforms

What audit-ready actually means for a digital health SDLC: a named artifact and system of record for every release gate, append-only evidence, and the difference between a regenerable record and a point-in-time one.

First-Party Security and Observability for Regulated Cloud SaaS

Designing observability for regulated cloud SaaS as audit evidence: an append-only, hash-chained event schema, direct first-party protocol boundaries instead of vendor APM/logging SDKs, and sovereign control over retention.

Production Incident Evidence, Root Cause Analysis & CAPA

Production incident evidence and CAPA (Corrective and Preventive Action) per ISO 13485:2016 §8.5.2 (former 21 CFR §820.100, replaced under the QMSR): root cause analysis, verified corrective action, scoped preventive action, and an effectiveness check.

Government Contract Delivery Traceability & Quality Assurance

Government contract delivery traceability: mapping CDRL items to specific dated artifacts and acceptance evidence, and why a program review deck is not a substitute for verifiable deliverable quality records.

Legacy Federal System Modernization Without Operational Stoppage

Modernizing legacy federal systems without an operational stoppage: the strangler-fig migration pattern, choosing seams at real architectural boundaries, and evidence-based cutover criteria instead of a fixed migration deadline.

Computing Paradigms: Protocol-First and Layer Minimization

Protocol-first engineering and layer minimization: the Bare Metal Software Complexity Ledger test ("would explicit SQL make behavior clearer?") applied to real architecture choices — no ORM, no bundler, no second language.

The Computing Paradigms: A Correctness and Governance Framework

The Computing Paradigms — deterministic-first, probabilistic-first, probability-infused deterministic, and deterministically-infused probabilistic — compared across correctness model, testing approach, evidence type, accountability, failure mode, and governance model.

Bare Metal Software: Software Sovereignty via Native Platforms

Software sovereignty per the Bare Metal Software fieldbook: the disappearance test, the Complexity Ledger, and a concrete SQLite + WAL + Litestream architecture that removes managed-database vendor dependency — with the authoritative Growth Ladder for climbing off it only on evidence.

The AI Workforce: Spec-Driven Harness Engineering

The AI Workforce operating model: spec-driven harness engineering where specifications are the source of truth, an AI harness implements against them, and humans supply thresholds, examples, and audits — not extra production hands.

AI Native Delivery Patterns for Tiny Engineering Teams

AI-Native delivery patterns for a one-developer engineering team: production ownership stays with the developer, an AI harness performs bulk implementation against specs, and leadership's five non-delegable jobs replace headcount growth.

Operational Truth™: Proof Over Promises in Engineering Evidence

Operational Truth™: the engineering discipline of continuous, machine-verifiable evidence over point-in-time attestation — what it means for audit trails, workflow definitions, and compliance evidence.

Automated Testing Strategy for Consequential Software Systems

A four-layer automated testing strategy for regulated and consequential software — what unit, integration, system, and acceptance tests each actually verify, and how a test run becomes traceable evidence rather than just a passing build.

CI/CD Pipelines as Audit Evidence for Regulated Change Control

CI/CD as audit evidence, not just deployment automation: what a regulated pipeline run needs to capture (commit, test results, build provenance, approval, deployment record) and why retention policy is where most pipelines quietly fail.

Threat Modeling for Consequential Systems: A Design-Time Discipline

Threat modeling as a design-time discipline for consequential systems: a systematic STRIDE-style elicitation frame, how identified threats feed the ISO 14971 risk management file, and a worked authentication-boundary example.

Observability for Consequential Systems: Evidence, Not Just Debugging

Observability reframed as evidence infrastructure for consequential systems: what logs, metrics, and traces each need to additionally answer beyond debugging, and how they feed root-cause analysis and queryable operational evidence.