Automated Open Source Software Reuse Scoring System
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Solution Overview
Problem
Current methods lack a dependable process for measuring the reusability of open-source software libraries, failing to consider real-world usage and functional reuse potential, which hinders effective software development and evolution.
Innovation Solution
A system and method that calculates a forked project reuse index based on useful forks, dependency consumption, and natural language processing to assess the reusability of open-source libraries by analyzing commit history, code attributes, and functional reuse, providing a unified reuse score.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional quality measurement systems are used to measure software library reuse, then code quality metrics can be obtained, but real-world usage and functional reuse potential are not considered
Solution Approach 1:
The patent segments the reuse measurement into multiple independent dimensions: fork-based reuse metrics, dependency-based reuse metrics, and functional reuse metrics. Each dimension is calculated separately using specific algorithms (e.g., fork activity analysis, dependency graph traversal, code similarity comparison) and then aggregated to form a comprehensive reuse score, allowing precise measurement of different aspects of reuse independently
Solution Approach 2:
The patent introduces a multi-dimensional measurement framework that adds new dimensions beyond traditional code quality metrics. It incorporates temporal dimension (fork activity over time), relational dimension (dependency relationships between projects), and functional dimension (code similarity and purpose). This dimensional expansion enables measurement of real-world usage patterns and functional reuse potential that single-dimensional traditional metrics cannot capture
2Productivity
If ad hoc development of reuse practices is used, then some reuse benefits can be achieved, but a dependable process model is lacking
Solution Approach 1:
The patent implements feedback mechanisms where reuse metrics are continuously calculated and fed back to developers and project maintainers. The system monitors fork activity, dependency usage, and code reuse patterns over time, providing quantitative feedback that informs future development decisions. This creates a closed-loop process where measurement results directly influence subsequent reuse practices, making the process dependable and iterative
Solution Approach 2:
The patent establishes a systematic framework with configurable parameters for measuring different aspects of reuse (e.g., time windows for fork analysis, similarity thresholds for code matching, weightings for different metric components). These parameters can be adjusted based on specific project needs and contexts, transforming ad hoc practices into a reliable, parameter-driven process model that adapts to different scenarios while maintaining consistency
3Measurement precision
If fork activity and dependency consumption are used to measure reuse, then real-world usage can be quantified, but measurement complexity increases
Solution Approach 1:
The patent extracts specific measurable indicators from complex real-world usage patterns, such as counting fork events, tracking dependency declarations, and measuring code similarity percentages. By focusing on these extractable, quantifiable signals rather than attempting to measure all aspects of reuse, the system achieves functional reuse measurement without requiring overly complex measurement infrastructure
Solution Approach 2:
The patent introduces intermediary metrics that bridge the gap between complex real-world usage and simple quantifiable measurements. For example, it uses fork activity counts as an intermediary to represent complex project forking behavior, dependency graph depth as an intermediary for complexity analysis, and code similarity percentages as intermediaries for functional equivalence assessment. These intermediaries simplify the measurement process while preserving the essence of functional reuse
Data Source
AI summary
Methods and systems for automated scoring of open-source libraries on their state of reuse in software projects are provided. A system is configured to extract information about the software project, determine whether the extracted information includes information regarding any forked projects, calculate a useful fork reuse score for a forked project, calculate a reuse score in the forked project based on source code attributes including a source code class, create a tree structure for the source code class, identify functions from the tree structure of the source code class, identify similar code sections from the two source code files, calculate a code attributes reuse score based on the similar code sections, calculate a dependent consumption reuse score which indicates how much a function is reused by a dependent class, and calculate a unified reuse score based on the reuse score of the forked project and the dependent consumption reuse score.