Dynamic Patch Queue Prioritization for Build Efficiency
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The existing First-In First-Out (FIFO) approach to managing software patch submissions in software development environments is inefficient, leading to slowed integration processes and potential delays in making working builds available for downstream operations, which can waste developer time and hinder business objectives.
Innovation Solution
An enhanced integration scheme that analyzes queued patches based on priority factors, allowing patches to be integrated in a non-chronological order, with priority adjustments for factors such as patch dependencies, testing status, geographic location, and business hours, ensuring that the highest priority patches are integrated first.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If patches are integrated in first-in first-out order, then the queue management is simple, but critical patches cannot be prioritized and integration efficiency is reduced
Solution Approach 1:
The patent implements dynamic patch prioritization by introducing a priority score system that evaluates multiple factors (criticality, dependencies, testing status, geographic location, business hours) to determine integration order. This transforms the static FIFO queue into a dynamic priority-based queue that adapts to changing conditions, resolving the contradiction between simple management and high efficiency.
Solution Approach 2:
The system changes the parameter of patch selection from chronological order to priority score-based order. By calculating and comparing priority scores for each patch based on multiple attributes, the system enables critical patches to be integrated ahead of less important ones, significantly improving integration efficiency while maintaining manageable complexity through automated scoring.
2Loss of time
If patches are integrated in chronological order, then the processing order is predictable, but wait time for critical patches increases
Solution Approach 1:
The system performs preliminary evaluation of each patch's attributes (criticality, dependencies, testing status, geographic location, business hours) before integration to assign priority scores. This preliminary analysis enables the system to predict and optimize the integration order, reducing wait time for critical patches while maintaining operational predictability through consistent scoring criteria.
Solution Approach 2:
The patent replaces the mechanical FIFO first-come-first-served system with an intelligent priority-based selection system. By substituting simple chronological ordering with multi-factor priority calculation, the system reduces wait time for critical patches while maintaining predictability through transparent and consistent priority scoring rules.
3Adaptability or versatility
If the build server processes patches in arrival order, then resource utilization is steady, but business priorities cannot be aligned
Solution Approach 1:
The patent segments the patch evaluation process into distinct attribute categories (criticality, dependencies, testing status, geographic location, business hours), each contributing to the overall priority score. This segmentation enables the system to align with business priorities by weighting different attributes appropriately, while keeping the evaluation system manageable through modular attribute assessment.
Solution Approach 2:
The priority evaluation system serves multiple functions simultaneously: it aligns integration order with business priorities, accounts for geographic and temporal constraints, manages patch dependencies, and optimizes resource utilization. This multi-functionality achieves high adaptability to business priorities while consolidating complexity into a single unified evaluation framework.
Data Source
AI summary
Queued software patches are analyzed before one patch is chosen as the next patch to be integrated into a working build. The chosen patch might not be next in chronological order of arrival at the queue. Instead, an illustrative build server applies a number of priority factors to every patch awaiting integration in the patch queue, specifically by analyzing one or more relevant attributes of the patch. The patch that receives the highest priority score in the course of the evaluation is then extracted for integration. After the patch has been integrated, the build server (e.g., using an illustrative patch queue manager module) circles back and again evaluates all the patches in the current queue, which may have queued new patches that were submitted while the previous patch was being integrated. Relative to a default chronological order, a given patch may receive a boost in priority or, conversely, may have its priority reduced.