Functional Use-Case Generation via Context Analysis
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Solution Overview
Problem
Deficiencies in requirements documents lead to incomplete and inaccurate functional use-case specifications, resulting in defects and increased costs during software design, coding, and testing, due to missing information about actors, start and end points, and sequence of steps, as well as incorrect rules and assumptions.
Innovation Solution
A functional use-case generation system and method that utilize a functional model repository to augment knowledge, including entities, tasks, and rules, with a requirements context analyzer to extract context from documents and search for best practices, and a process context analyzer to provide relevant information for generating accurate and complete functional use-cases.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual functional use-case specification is performed based on requirements documents, then flexibility and adaptability are maintained, but accuracy and completeness deteriorate due to human error and missing information
Solution Approach 1:
The patent introduces an intermediary system comprising a requirements context analyzer, process context analyzer, and functional model repository that mediates between the requirements document and the functional use-case specification. This intermediary automatically extracts context, identifies processes and entities, and generates use-cases, thereby improving accuracy while managing complexity through automation.
Solution Approach 2:
The patent replaces the manual mechanical process of functional use-case specification with an automated computer-based system. The system uses algorithms to analyze requirements documents, extract context, and generate functional use-cases automatically, eliminating human error and improving reliability.
2Reliability
If detailed manual analysis of requirements documents is performed to ensure completeness, then accuracy improves, but time consumption and productivity deteriorate
Solution Approach 1:
The patent replaces time-consuming manual analysis with automated computer-based analysis. The requirements context analyzer and process context analyzer rapidly process requirements documents using algorithms, extracting all necessary context and generating complete functional use-cases much faster than manual methods while maintaining completeness.
Solution Approach 2:
The patent enables continuous automated analysis of requirements documents without the interruptions inherent in manual processes. The system continuously extracts context, identifies processes and entities, and generates functional use-cases in an uninterrupted workflow, significantly improving productivity while ensuring completeness through systematic coverage.
3Loss of information
If functional use-cases are generated without a functional model repository, then process simplicity is maintained, but information loss and accuracy deteriorate
Solution Approach 1:
The patent implements a nested structure where the functional model repository is embedded within the larger system architecture. The repository contains functional models that are nested within the context of specific requirements documents and use-case specifications, allowing information to be retained at multiple levels without overwhelming system complexity.
Solution Approach 2:
The functional model repository serves as an intermediary layer between the requirements document and the generated functional use-cases. It stores and manages functional models, entities, and rules, preventing information loss while managing complexity through structured organization and automated retrieval.
4Productivity
If automated functional use-case generation is implemented, then productivity improves, but device complexity and resource utilization worsen
Solution Approach 1:
The patent segments the automated functional use-case generation system into distinct modular components: a requirements context analyzer module, a process context analyzer module, a functional model repository, and a use-case generation module. Each module performs a specific function, improving productivity through automation while managing complexity through modular design that allows independent development and maintenance.
Data Source
AI summary
Functional use-case generation may include determining whether a requirements context is available. In response to a determination that the requirements context is available, the requirements context may be determined as a task context and as a rule context for a requirements sentence of a requirements document. The task context and the rule context may be used to select a functional model from a plurality of functional models. A functional use-case that includes an entity that is to perform a task based on a rule may be generated. Further, in response to a determination that the requirements context is not available, a functional model may be selected from the plurality of functional models based on process context, where the functional model includes a process related to the process context, and the functional model that includes the process related to the process context may be used to generate the functional use-case.