Research Evidence Index
GAO-25-107283 — Defense Industrial Base: Actions Needed to Address Risks Posed by Dependence on Foreign Suppliers
GAO documents persistent limitations in defense supply-chain visibility, especially below prime and tier-one levels. SALAR uses this public evidence as context for graph-based lower-tier dependency analysis and common-mode exposure mapping.
GAO-26-107882 — Semiconductors: Information on Projects Funded to Strengthen U.S. Supply Chain
GAO documents the scale and breadth of U.S. semiconductor industrial-base investment across the supply chain. SALAR uses this source as context for resilience, qualification, capacity, and dependency analysis.
NIST SP 800-161 Rev. 1 — Cybersecurity Supply Chain Risk Management Practices
NIST provides an established framework for supply-chain risk management across systems and organizations. SALAR's public SCRM material aligns its evidence-to-decision structure with this broader risk-management discipline without claiming NIST certification.
NASA EEE-INST-002 — EEE Parts Selection, Screening, Qualification and Derating
NASA establishes baseline criteria for selection, screening, qualification and derating of electrical, electronic and electromechanical parts. SALAR cites this type of guidance when explaining why part stress and derating matter in mission-critical reliability.
NASA Systems Engineering Reliability Guidance
NASA reliability resources emphasize parts assessment, performance, failure modes, test methods, derating and supply-chain quality. SALAR uses these principles as external technical context for electronics reliability reviews.
NIST — Cybersecurity Supply Chain Risk Management Publications
NIST's C-SCRM publication library provides current federal guidance, including due-diligence and supplier-risk resources. SALAR uses this as a living reference point for supply-chain assurance terminology and evidence practices.
IETF Draft — AI Fabric Training Benchmarking
The draft defines vendor-independent terminology and benchmarking concepts for Ethernet AI training fabrics, including RoCEv2/UET, PFC, ECN, ECMP, collectives and scale testing. SALAR uses these public concepts to frame cross-layer AI-fabric validation.
NIST IR 8536 — Supply Chain Traceability Principles
NIST's traceability work describes provenance, pedigree and verifiable supply-chain event data as tools for reducing blind spots. SALAR uses that public framing for evidence-governed provenance and source-confidence analysis.