Requirements Tracing Validation Tool for Avionics
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional requirements tracing tools in certified software-based airborne systems only verify the existence of links between subsystem and higher-level requirements, failing to assess their correctness or identify missing links, which is critical for ensuring the quality and completeness of requirements tracing in system-critical avionics software.
Innovation Solution
A requirements tracing validation tool that utilizes a natural language engine to identify high-level and subsystem-level requirements, evaluates the correctness of existing links, and recommends additional links based on linguistic and logical components, providing a confidence level for the correctness of these links, and suggests wording modifications to improve clarity and accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional requirements tracing tools are used to verify the existence of links between subsystem and higher-level requirements, then the basic traceability is ensured, but the correctness and quality of the links cannot be assessed
Solution Approach 1:
The patent replaces conventional mechanical/link-based traceability verification with a natural language processing system that uses linguistic analysis to assess link correctness. The NLP engine analyzes the textual content of requirements and traces to determine semantic correctness, moving from simple existence verification to intelligent semantic validation.
Solution Approach 2:
The patent introduces a natural language engine as an intermediary between the requirements traceability system and the verification process. This intermediary uses linguistic analysis to bridge the gap between structural traceability and semantic correctness, enabling automated assessment of link quality without requiring complex manual verification.
2Reliability
If conventional tracing tools only verify link existence, then the tool complexity is low, but the completeness of requirements tracing cannot be ensured
Solution Approach 1:
The patent implements a feedback mechanism where the NLP engine continuously analyzes traces and provides assessments of correctness and completeness. The system identifies orphan requirements and incomplete traces, then feeds this information back to users to guide corrections, ensuring complete and accurate traceability coverage.
Solution Approach 2:
The system performs self-verification by automatically analyzing its own traceability links using NLP techniques. It independently assesses the correctness of traces and identifies gaps without requiring external manual verification, enabling the system to self-validate its traceability quality.
3Measurement precision
If manual verification of requirements traces is performed, then the accuracy of link correctness can be ensured, but the time and labor required increase significantly
Solution Approach 1:
The patent substitutes manual verification processes with an automated NLP-based system that uses natural language understanding to assess trace correctness. This replacement eliminates the need for human analysts to manually review each trace, significantly reducing verification time while maintaining high accuracy through intelligent linguistic analysis.
Solution Approach 2:
The system changes the verification parameter from binary link existence (conventional) to semantic correctness assessment (NLP-based). By analyzing the linguistic content and semantic relationships within traces, the system provides graded accuracy assessments that reflect the true quality of traceability links.
Data Source
AI summary
A requirements tracing validation tool analyzes an input corresponding to a requirements tracing set to identify high-level requirements and artifacts, subsystem-level requirements and artifacts, current links tracing between the requirements and the artifacts, and linguistic and logical elements of each identified artifact or link. The tool evaluates each link and provides a confidence level as to the correctness of the link. The tool may recommend additional links not already within the set and evaluate the recommended links for correctness. Further, the tool may evaluate the correctness of a given requirement over time as the requirements tracing set and its environment develops, and offer suggestions for amending the wording of artifacts and links to enhance uniformity and clarity throughout the requirements tracing set and increase the likely correctness of all traces and links within the environment.