IV&V Test Analysis

Overview

Development stage

In development or acquisitionSource: a) Pre-deployment – The use case is in a development or acquisition status.

High-impact designation

Not high-impactSource: c) Not high-impact

Impact justification

Not reported

Start date

Not reported

Withheld from public reporting

NoSource: a) No

Mission

Topic area

Science

Operational functions

No function tag matched Derived by keyword rules; see methodology

Problem the AI is intended to solve

This project develops software to generate pre-computed, draft analysis results for text-based test artifacts on NASA programs within the scope of Independent Verification & Validation (IV&V). The software provides a web-based interface that enables users to filter pre-computed findings by issue severity, evaluate and provide feedback for generative AI–produced results, and auto-draft IV&V issues. Its analysis capabilities include assessment of tests for completeness and consistency. Initial development and testing will utilize limited synthetic data or open source data hosted on AWS (Cloud – Other). Beginning in FY26, the project will transition to beta and production phases, operating on local on-premises HPC infrastructure with access to real ITAR-level NASA mission data.

Expected benefits

Implementation of the local on-premises HPC environment and subsequent execution of AI-enhanced IV&V analysis activities will begin in FY26. These activities will be complemented by expert human engineering judgement and further analysis. By integrating AI-generated content into NASA IV&V's current processes, analysis results and assessments can be produced significantly faster than with traditional methods. This accelerated capability is expected to positively impact the mission projects supported by NASA IV&V by enabling earlier identification of issues, more thorough characterization of residual risk and impact of any open identified issues, and delivery of improved, risk-informed decision-making support to programs.

System outputs

Simiilar to Requirements Analysis or borrowing a same feature set, the AI system (Web UI-based) will provide an assessment (recommendations) output on test cases, procedures, or steps, highlighting any potential issues to the analyst reviewer. Analysts will also have the opportunity to autogenerate draft issues, provide feedback on the results through buttons and comment boxes, and export results to a spreadsheet.

Technology

AI classification

Generative AISource: Generative AI: AI that generates new or synthetic content (e.g., images, videos, audio, text, code).

System name(s)

Not reported

Custom-developed code

Not reported

Public source code

Not reported

Sourcing

How it was built

Not reported

Vendor (as reported)

Not reported

Vendors (standardized)

None on the standard list

A vendor is the supplier named by the agency. It does not identify the underlying model or AI technology.

Data and privacy

Involves PII

Not reported

Privacy Impact Assessment

Not reported

Authorization to Operate

Not reported

Demographic features

Not reported

Training and evaluation data

Not reported

Federal Data Catalog

Not reported

Governance

0 of 8 minimum-practice questions answered. A blank answer means the agency reported nothing; it does not mean the practice is absent.

Potential impacts and how they were identified

Not reported