Concept Detection System for Software Code Quality
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Solution Overview
Problem
Current software development tools are limited in their ability to detect and address concept violations across different components, failing to capture design and architectural abstractions, and provide actionable feedback for improving code quality.
Innovation Solution
A graphical user interface is used to specify complex concepts in rule form, allowing for the detection of violations and providing recommendations for code transformation, enabling users to define and reconfigure concepts applicable to specific projects, and facilitating analysis across the entire software system.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing code analysis tools are used, then basic code quality checks can be performed, but they fail to capture design and architectural abstractions and cannot detect concept violations across different components
Solution Approach 1:
The system transitions from static, pre-defined concept detection to dynamic, user-configurable concept specification. Users can define custom concepts through a graphical interface that captures design and architectural abstractions, allowing the detection system to adapt to specific project requirements and detect violations across different components with higher precision.
Solution Approach 2:
The invention changes the parameters of concept detection by allowing users to specify concepts at multiple levels of abstraction (design, architecture, application-domain) rather than being limited to fixed code-level checks. This enables detection of cross-component violations and captures nuanced design patterns specific to each project.
2Extent of automation
If existing tools with pre-defined knowledge bases are used, then concept detection can be performed automatically, but users cannot enrich or customize the knowledge base for their specific projects
Solution Approach 1:
The system enables users to self-configure and enrich the concept detection knowledge base through an intuitive graphical interface. Users can define their own concepts, specify detection rules, and customize the analysis scope without requiring manual intervention from developers or system administrators, maintaining automation while enabling customization.
Solution Approach 2:
The system performs preliminary analysis by examining code snippets provided by users to automatically generate concept definitions and detection rules. This preliminary action reduces the effort required from users to configure the system, as the tool pre-processes sample code to suggest appropriate concept specifications before final user confirmation.
3Loss of information
If existing tools provide violation reports, then concept violations can be identified, but they fail to indicate the impact of violations or specify corrective actions
Solution Approach 1:
The system implements comprehensive feedback by analyzing the impact of detected concept violations on software quality attributes and providing specific corrective recommendations. The graphical interface presents violation information in context, showing how violations affect design principles, architectural constraints, or domain-specific requirements, and suggests actionable steps for remediation.
Solution Approach 2:
The invention adds dimensional depth to violation reporting by analyzing concepts across multiple levels of abstraction simultaneously (code, design, architecture, application-domain). This multi-dimensional analysis provides more complete information about violation impact without proportionally increasing system complexity, as the same core engine handles all levels.
4Measurement precision
If concept detection is limited to code level, then detection is straightforward, but design and architectural concepts cannot be captured
Solution Approach 1:
The system segments concept detection into distinct levels of abstraction (code, design, architecture, application-domain), allowing each level to be analyzed with appropriate methods and rules. This segmentation enables capture of high-level design and architectural concepts while maintaining the precision needed for code-level detection, with the graphical interface managing the complexity of coordinating analysis across all levels.
Data Source
AI summary
Techniques enabling an end-user to specify complex concepts consisting of code abstractions, design abstractions and architectural abstractions in rule form are disclosed. In one embodiment, a graphical user interface is provided to guide a user through the process of entering concept specification information in order to define concepts, including the provision of one or more code snippets that are subsequently analyzed to assist the user in specifying the concept. The resulting rules or concept signatures are evaluated by a rule engine to determine the degree to which the underlying concepts are reflected in a given set of code. Recommended measures that need to be taken for transforming code to satisfy a concept may be provided subsequent to the analysis of the code. In this manner, code quality may be improved through systematic analysis of targeted code to demonstrate adherence (or non-adherence, as the case may be) to user-defined concepts.