JSON Delta Generation via Property Segmentation
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Solution Overview
Problem
Existing methods for comparing and merging JSON documents are inefficient, as they often result in larger delta files that are not human-readable and can contain redundant information, making them error-prone and less efficient.
Innovation Solution
The system generates delta object notation documents by comparing two JSON documents, identifying changes such as additions, deletions, and type changes, and representing these changes in a JSON format that is human-readable and efficient, allowing for the creation and merging of delta files into a single, optimized document.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If existing methods are used to compare and merge JSON documents, then the comparison function is achieved, but the delta files become large, non-human-readable, and contain redundant information
Solution Approach 1:
The patent segments the JSON document comparison into identifying only the minimal set of changed properties (additions, deletions, modifications) rather than comparing entire documents. This segmentation produces compact delta files that contain only essential change information, reducing file size while maintaining human-readability through structured representation of changes.
Solution Approach 2:
The patent extracts only the necessary change information from full JSON document comparisons, removing redundant unchanged properties. By taking out only the delta (changes) rather than including complete document representations, the method achieves smaller file sizes while preserving readability through focused presentation of actual modifications.
2Reliability
If existing comparison methods are used, then all changes are captured, but redundant information increases file size and reduces efficiency
Solution Approach 1:
The patent extracts only the essential change information (additions, deletions, modifications) from JSON document comparisons, eliminating redundant unchanged properties. This extraction process maintains complete change detection accuracy while significantly reducing the volume of delta file content by including only what is necessary to represent the changes.
Solution Approach 2:
The patent changes the representation parameters from full document comparison to selective property-level change detection. By parameterizing the comparison to focus only on changed properties rather than all properties, the method achieves accurate change detection with minimized data volume in the delta files.
3Productivity
If traditional delta generation is used, then changes are recorded, but the delta files are error-prone and less efficient to apply
Solution Approach 1:
The patent segments delta representation into distinct, well-defined change types (additions, deletions, modifications) with explicit property-level granularity. This segmentation reduces errors by clearly delineating what changed and how, making delta files more reliable and efficient to apply compared to traditional monolithic delta representations.
Solution Approach 2:
The patent changes the delta representation parameters to use explicit property-level change records with clear operation types rather than implicit or monolithic change representations. This parameter change improves reliability by reducing ambiguity and increases productivity by enabling more efficient parsing and application of changes.
Data Source
AI summary
The present disclosure involves systems, software, and computer implemented methods for creating and merging delta object notation documents. One example method includes receiving a request to create a delta object notation document based on a first object notation document and a second object notation document. The first object notation document is compared to the second object notation document to generate the delta object notation document in an object notation format. Generating the object notation document includes navigating properties in the first object notation document and the second object notation document to identify properties in the first object notation document and the second object notation document and determining, for each property identified in the first object notation document or the second object notation document, whether a property with a same name and parent exists in a corresponding first object notation document or a corresponding second object notation document.