Code Change Prioritization via Merging Similar Requests
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Solution Overview
Problem
Current systems for managing code change requests are resource-intensive, inefficiently process requests in sequence, leading to overtaxed processing power, redundant modifications, and suboptimal memory usage, failing to prioritize requests based on severity and impact, and require multiple code base openings for similar changes.
Innovation Solution
A code change request prioritization system that assigns a total weighted percentile score to each request using various factors, identifies high-priority requests, and uses machine learning to detect similar requests, allowing for simultaneous resolution across multiple code bases.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If code change requests are processed in sequence of receipt, then each request is handled individually, but processing time increases and productivity decreases
Solution Approach 1:
The patent merges multiple similar code change requests into a single consolidated request. The system identifies requests that affect the same code base or similar code patterns and combines them into one unified change operation, thereby reducing the total number of separate processing operations and decreasing overall processing time while maintaining productivity.
Solution Approach 2:
The patent performs preliminary analysis and grouping of code change requests before actual processing. By pre-identifying similar requests and consolidating them in advance, the system prepares optimized batch operations that reduce subsequent processing time and improve resolution efficiency.
2Device complexity
If each code change request is handled individually, then processing is simple, but processing power is overtaxed and resource usage increases
Solution Approach 1:
The system combines multiple individual code change operations into consolidated batch operations. By merging similar requests that modify the same code base or follow similar patterns, the system reduces the total number of separate processing tasks, thereby lowering processing power consumption while maintaining manageable complexity through automated identification and grouping.
3Quantity of substance
If code change requests are processed sequentially, then resource usage is manageable, but memory space is reduced and computer optimizations are degraded
Solution Approach 1:
The system performs preliminary consolidation of code change requests before processing, grouping similar requests together in advance. This pre-processing step organizes the workload into optimized batches that can be executed more efficiently, improving code optimization efficiency while managing memory space through structured batch processing rather than individual sequential operations.
4Reliability
If similar code change requests are not identified, then each request is processed separately, but redundant modifications occur and processing efficiency decreases
Solution Approach 1:
The system identifies and merges similar code change requests by analyzing code patterns, affected files, and change types. This consolidation ensures that similar modifications are performed once rather than redundantly multiple times, improving code modification accuracy by preventing duplicate changes while significantly improving resolution efficiency through reduced processing overhead.
5Ease of operation
If multiple code bases are opened separately for similar changes, then each code base is handled independently, but processing time increases and productivity decreases
Solution Approach 1:
The system merges processing operations across multiple code bases by identifying similar change patterns. Instead of opening and processing each code base separately, the system consolidates similar operations into unified batch processing tasks that can be applied across multiple code bases simultaneously or in optimized sequences, thereby maintaining operational simplicity while significantly reducing total processing time.
Data Source
AI summary
A code change request prioritization tool that uses weighting values specific to pre-determined factors to concurrently calculate a total weighted prioritization score, is disclosed. The total weighted prioritization score may be calculated using a percentile score for factors as inputs in the calculation. Once a solution is found for a highest priority code change request, similar code defects may be identified so as to provide solutions to all similar defects, simultaneously.


