Evolvable Software Component Compositions Using Change Signatures
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Solution Overview
Problem
Current software development methods lack automation for systematically designing evolvable and reusable software components, relying heavily on manual processes and lacking systematic methods to capture, codify, and reuse information about change to facilitate rapid and cost-effective solution evolution.
Innovation Solution
A computer-implemented method and system that analyzes textual requirement statements to automatically generate evolvable compositions of reusable software components by partitioning required elements into multi-level components, using change signatures and indexes to identify impacted components, and providing automated guidance for decision-making.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual processes are used to design software components, then flexibility and adaptability are maintained, but productivity and consistency are reduced
Solution Approach 1:
The system performs self-service by automatically analyzing requirement statements, identifying solution elements, and generating component designs without requiring manual intervention at each step. The automated analysis engine processes requirements and generates component compositions independently, reducing the need for manual design work while maintaining high productivity and consistency.
Solution Approach 2:
The patent replaces manual mechanical processes with an automated computational system. The automated analysis engine substitutes human analysts by using computational methods to parse requirement statements, identify solution elements, and determine component compositions, thereby increasing productivity while managing system complexity through algorithmic approaches.
2Adaptability or versatility
If information about change is systematically captured and codified, then adaptability and reuse are improved, but loss of time for information gathering and processing increases
Solution Approach 1:
The system performs preliminary action by capturing and codifying information about change during the initial requirements analysis phase. The automated analysis engine identifies solution elements and their relationships early in the process, storing this information in a structured format that can be quickly retrieved and applied during solution evolution, thereby reducing later information processing time while maintaining high adaptability.
3Manufacturing precision
If automated analysis is implemented to generate component compositions, then manufacturing precision and reliability are improved, but device complexity increases
Solution Approach 1:
The patent applies segmentation by dividing the automated analysis system into distinct functional modules: a requirement statement parser, a solution element identifier, and a component composition generator. Each module performs a specific function with well-defined inputs and outputs, which improves manufacturing precision through specialized processing while managing overall system complexity through modular architecture.
Solution Approach 2:
The system utilizes parameter changes by adjusting the level of automation and analysis depth based on specific project requirements. The automated analysis engine can operate at different levels of detail, changing parameters such as the granularity of component analysis and the extent of automated generation, thereby achieving high precision when needed while controlling system complexity through configurable parameters.
Data Source
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AI summary
A computer-implemented method and system that systematically and analytically uses information about change to design evolvable compositions of reusable software components (modules and other units of software encapsulation) for the development of evolvable software solutions. The invention provides a computerized framework for identifying, capturing, encoding, codifying, learning, verifying, applying, and reusing information acquired through requirements and design analyses to systematically determine compositions of reusable components that localize the impact of expected and feasible or feasible (EFF) change, promote reuse, and thereby can help lower the cost associated with software evolution.