Programming Data Contribution Rate Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing technologies fail to clearly distinguish the contributions of programmers, automatic code generation tools, and programming platforms to programming efficiency and quality, as their behaviors and functions are not effectively differentiated during the programming process.
Innovation Solution
A method and device that acquire and analyze programming data to identify programming behaviors and determine contribution rates of programmers, automatic code generation tools, and programming platforms by monitoring key operations and tracking entered, recommended, and deleted codes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automatic code generation tools and programming platforms are used to assist programmers, then programming efficiency is improved, but it becomes difficult to distinguish the contribution of each component (programmer, tool, platform) to the final result
Solution Approach 1:
The patent segments the programming process into distinct phases (code entry, code recommendation, code deletion) and attributes contributions to different sources (programmer, automatic code generation tool, programming platform) separately. This segmentation allows tracking and quantifying the contribution of each component independently while maintaining overall programming efficiency.
Solution Approach 2:
The patent introduces a behavior identification mechanism as an intermediary that mediates between the programming process and contribution assessment. This intermediary tracks and records the behavior data of programmers, tools, and platforms, enabling accurate contribution distinction without interfering with the actual programming workflow.
2Measurement precision
If comprehensive monitoring of programming operations is implemented to assess contributions, then contribution assessment accuracy is improved, but system complexity increases
Solution Approach 1:
The patent extracts only the necessary behavior data (code entry, recommendation, deletion operations) from the complex programming process, rather than monitoring all system activities. This extraction approach maintains high measurement precision for contribution assessment while avoiding the complexity of comprehensive system-wide monitoring.
Solution Approach 2:
The patent applies different monitoring strategies to different components of the programming process. Instead of uniform comprehensive monitoring, it focuses local quality of monitoring on specific key operations (code entry by programmers, code recommendations by tools, code deletions) that are most relevant to contribution assessment, thereby reducing overall system complexity.
Data Source
AI summary
The present disclosure discloses a method and a device for processing programming data. The method includes: acquiring programming data of a target object; identifying a programming behavior of the target object according to the programming data; and determining programming contribution rates of the target object, an automatic code generation tool and a programming platform according to the programming behavior.