Automated Product Requirement Evaluation System
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Solution Overview
Problem
Drafting high-quality product requirements for complex products is challenging due to the risk of errors, incompleteness, or ambiguity, which can lead to higher costs, longer schedules, and performance risks.
Innovation Solution
A computing system that evaluates product requirements by identifying requirement types, determining required elements, performing natural language processing, and applying element identification rules to ensure completeness and accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual review processes are used to evaluate product requirements, then evaluation thoroughness can be maintained, but time consumption and labor effort increase significantly
Solution Approach 1:
The patent replaces manual mechanical review processes with an automated computing system that uses natural language processing models and machine learning algorithms to evaluate product requirements. The system automatically performs syntax parsing, semantic analysis, and compliance checking, eliminating the need for human reviewers to manually examine each requirement while maintaining evaluation thoroughness through systematic rule-based and model-based analysis.
Solution Approach 2:
The system enables product requirements to be self-evaluated through automated processing. The computing system independently analyzes requirements against predefined criteria, standards, and rules without requiring external human intervention. The automatic generation of evaluation reports and identification of issues allows the requirement documentation process to self-correct and self-validate, reducing dependency on manual review resources.
2Reliability
If comprehensive element checking is performed on product requirements, then requirement quality improves, but processing complexity increases
Solution Approach 1:
The patent segments the comprehensive requirement evaluation process into distinct modular components: syntax analysis module, semantic analysis module, compliance checking module, and report generation module. Each module handles specific aspects of requirement validation independently. The system divides complex requirements into individual elements for targeted analysis, applying different processing rules to different requirement types (functional, performance, interface, etc.), thereby managing processing complexity through structured decomposition while maintaining thorough quality checking.
3Productivity
If automated evaluation systems are implemented, then processing speed increases, but system complexity increases
Solution Approach 1:
The patent implements a universal computing system architecture that handles multiple requirement evaluation tasks through a single integrated platform. The system universally processes different types of product requirements (functional, performance, interface, design) using the same core NLP engine and evaluation framework. This multi-functional approach allows the system to achieve high processing speed across diverse requirement types without requiring separate specialized systems for each requirement category, thereby managing system complexity through consolidation rather than proliferation of separate tools.
Data Source
AI summary
A computing system for evaluating a product requirement is provided, including a processor configured to store input text of the product requirement. The processor is configured to identify a requirement type for the input text from among a plurality of candidate requirement types and determine a plurality of required elements for the identified requirement type from among a plurality of candidate elements, using a predefined requirements rubric. The processor is further configured to perform natural language processing on the input text to apply tags from a predefined tagset to respective portions of the input text to generate tagged input text. The processor is further configured to apply predefined element identification rules to the tagged input text to identify a presence or absence of each required element in the input text for the product requirement and output an indication of the identified presence or absence of each required element.