Rule-Based Technical Debt Scoring for Software Quality Control
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Solution Overview
Problem
Existing technologies fail to effectively manage and mitigate technical debt, leading to increased costs, product defects, and unpredictable device performance due to sub-optimal production practices.
Innovation Solution
A computer-implemented method and system for generating a technical debt management machine that automatically identifies and quantifies technical debt using rule-based artificial intelligence, displaying scores and remediation strategies through a user interface.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If sub-optimal production practices are used to reduce production cost or increase production speed, then production cost decreases or production speed increases, but technical debt increases leading to increased maintenance cost and product defects
Solution Approach 1:
The system performs preliminary analysis of code during the development phase to identify technical debt indicators before they become critical problems. By detecting issues early in the development process rather than after deployment, the system enables remediation at a stage when fixes are less costly and less disruptive to production operations.
Solution Approach 2:
The system continuously monitors code changes and automatically calculates technical debt scores, providing real-time feedback to development teams. This feedback loop enables teams to understand the impact of their coding decisions on technical debt and adjust their practices accordingly, balancing speed of delivery with code quality.
2Reliability
If comprehensive testing is performed to identify and repair faults, then product quality improves, but production time increases
Solution Approach 1:
The system performs preliminary automated analysis of code to identify potential defects and technical debt indicators before formal testing begins. This preliminary detection phase filters out many obvious issues that would otherwise require manual testing to discover, allowing testing resources to focus on more complex scenarios.
Solution Approach 2:
The system replaces manual code review and testing mechanics with automated computational analysis. Machine learning models and rule-based systems automatically scan code for technical debt patterns, replacing time-consuming human analysis with faster automated processes that can operate continuously without fatigue.
3Productivity
If technical debt is not monitored and managed, then development speed is maintained, but maintenance costs increase and device performance becomes unpredictable
Solution Approach 1:
The system implements continuous monitoring that provides ongoing feedback about technical debt accumulation. By tracking metrics such as code complexity, duplication, and deviation from best practices, the system alerts development teams when technical debt reaches threshold levels, enabling proactive management rather than reactive firefighting.
Solution Approach 2:
The system enables development teams to self-manage technical debt by providing them with actionable insights and prioritized remediation recommendations. Teams can autonomously address technical debt issues based on business priorities without requiring external intervention, making the management process efficient and integrated into normal development workflows.
Data Source
AI summary
Provided are methods and apparatus for generating at least a portion of a technical debt management machine. In an example, a computer-implemented method includes (i) comparing, by at least one processor and by automatically searching using a rule engine, information in at least a portion of an object in a software platform to a rule to identify a violation of the rule, where (a) the rule describes at least one information characteristic whose presence in an object being scanned indicates technical debt and results in the violation of the rule; and (b) the rule describes an amount that a technical debt score must be changed for the violation; (ii) changing, responsive to the violation, the technical debt score by the amount the technical debt score must be changed for the violation; and (iii) displaying, by a user display device and via a user interface, the technical debt score.