Selective Software Patching via Feature Usage Analysis
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Solution Overview
Problem
Existing software patching methods often result in excessive downtime and costs due to the need to patch all clients with a particular feature, regardless of usage, leading to unnecessary updates and delays in database access.
Innovation Solution
A method and system that utilize usage information to determine applicability requirements for patches, allowing patches to be selectively applied only to features that meet specific usage criteria, thereby reducing unnecessary downtime and resource allocation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If all clients with a feature are patched, then security vulnerabilities are addressed, but total downtime becomes excessive and costly
Solution Approach 1:
The patent applies local quality by selectively patching only those clients where the feature is actually used, rather than patching all clients uniformly. The system determines usage information for the feature and applies patches only to clients meeting the applicability requirements, thereby reducing unnecessary downtime while still addressing security vulnerabilities where needed.
Solution Approach 2:
The patent changes the parameter of patching scope from universal (all clients) to selective (only clients meeting usage criteria). By introducing applicability requirements based on usage information, the system transforms the patching process into a conditional operation that adjusts its scope based on actual feature usage patterns.
2Reliability
If all clients with a feature are patched, then all potential vulnerabilities are fixed, but resource allocation becomes inefficient
Solution Approach 1:
The patent extracts the unnecessary patching operations by identifying and excluding clients where the feature is not used. The system determines usage information and selectively applies patches only to clients meeting applicability requirements, thereby removing wasteful resource allocation while maintaining vulnerability coverage for actually used features.
Solution Approach 2:
The patent applies local quality by directing patching resources only to specific clients where the feature is actively used, rather than distributing resources uniformly across all clients. This selective approach optimizes resource allocation by focusing effort where it is most needed - on clients with actual feature usage.
3Productivity
If usage information is collected and applicability requirements are determined, then selective patching is enabled, but system complexity increases
Solution Approach 1:
The patent applies preliminary action by collecting usage information and determining applicability requirements before the actual patching process. This pre-processing step enables selective patching by establishing the criteria upfront, thereby improving patching efficiency while managing system complexity through structured preparation.
Solution Approach 2:
The patent uses feedback from usage information collection to drive the patching decision process. By determining applicability requirements based on actual usage patterns, the system creates a feedback loop that adapts the patching process to real-world conditions, improving efficiency while managing complexity through data-driven decision making.
Data Source
AI summary
A method for applying patches to one or more applications is provided. The method includes receiving a patch for a feature where the patch includes applicability requirements. The applicability requirements detail requirements that should be met for the patch to be applied. Usage information for the feature is then determined. For example, it is determined if a feature has been used by a client. The patch is then applied to an application if the usage information meets the applicability requirements for the feature.