Tree-Structured Software Matching for Scalable Asset Identification

The patent segments the database of known software into multiple subsets based on different properties (e.g., software type, version range, platform). Instead of testing against the entire database, the system divides the search space into manageable segments and tests inventory data against relevant subsets only, significantly reducing computational resources while maintaining identification accuracy.

The patent applies local quality by selecting and testing only the specific subsets of software rules that are relevant to the given inventory data. The system determines which subsets to test based on the properties of the inventory data (such as operating system, software category), thereby focusing computational effort only where necessary rather than exhaustively searching the entire database.

The patent segments the expanded database into multiple property-based subsets. Even though the database covers comprehensive software variations, the segmentation allows the system to quickly navigate to relevant subsets based on inventory data properties, reducing search time despite the larger overall database size.

The patent implements preliminary action by pre-organizing the database into subsets based on software properties before actual identification occurs. This pre-structuring allows the system to quickly determine which subsets to test without having to search through the entire database, thus maintaining fast identification times even with comprehensive software coverage.

The patent segments the software inventory processing into separate stages: first grouping inventory data by device properties (operating system, hardware architecture), then testing against corresponding software subsets. This segmentation allows the system to handle multiple devices with different software utilizations by processing them through standardized segmented stages rather than as a monolithic complex process.

The patent creates a universal processing framework that can handle diverse device types and software configurations through the same segmented approach. The system uses a multi-functional rule-testing mechanism that works across different device platforms by selecting appropriate subsets, thereby managing complexity through a unified universal process rather than device-specific procedures.