Software Diligence Metrics Using Code and Financial Data
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Solution Overview
Problem
Existing methods for assessing software developer productivity are cumbersome, limited in scope, and pose security risks, leading to incomplete evaluations and potential data breaches.
Innovation Solution
A computer-automated system integrating technical and financial metrics to evaluate software developer productivity, using complexity analysis, sentiment analysis, and outlier detection, with secure data integration and synthesis of dashboards and reports.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If manual data entry and integration processes are used to assess developer productivity, then comprehensive information can be obtained, but the process becomes cumbersome and error-prone
Solution Approach 1:
The patent replaces manual mechanical data entry and integration processes with automated computer-based systems. The system automatically collects technical metrics from code repositories, integrates financial data from HR systems, and generates productivity assessments without manual intervention, eliminating errors and reducing operational burden while maintaining information completeness
Solution Approach 2:
The patent creates a multi-functional system that simultaneously performs data collection from multiple sources, technical metric analysis, financial data integration, productivity calculation, and report generation. This universal system handles the entire diligence process in one automated workflow, improving both ease of operation and information completeness
2Loss of information
If traditional data systems are used to analyze developer productivity, then data can be processed, but security risks and potential data breaches occur
Solution Approach 1:
The patent introduces secure intermediary mechanisms including encrypted data transmission channels, authenticated API interfaces, and controlled access protocols between different data sources and the analysis system. These intermediaries protect sensitive developer and financial data while enabling efficient automated processing, resolving the conflict between security and productivity
3Measurement precision
If existing technical metrics systems are used to assess developer productivity, then code quality can be measured, but financial impact and economic value are not captured
Solution Approach 1:
The patent merges technical metrics systems with financial data systems into a unified assessment framework. It combines code quality measurements, productivity indicators, and financial impact data (salaries, bonuses, revenue contribution) into a comprehensive model that simultaneously evaluates technical performance and economic value, enhancing both measurement precision and assessment scope
Data Source
AI summary
One embodiment of the present invention relates to a computer-automated system and method for evaluating software development metrics to enhance the diligence process and detect source code plagiarism. The system integrates technical and financial metrics to assess the productivity and economic impact of software developers. It includes a plurality of data sources, such as work product data sources containing source code and financial data sources detailing compensation. The system processes and analyzes this data to generate outputs reflecting worker performance and financial efficiency. Key features include complexity analysis of source code, sentiment analysis, and outlier detection in financial transactions. The system provides synthesized outputs, such as dashboards and reports, which are reviewed and approved before being shared with requesters. This invention offers a comprehensive, secure, and efficient approach to quantifying developer contributions, facilitating better investment decisions and operational assessments within the software development industry.