Graph-Based Divergent Information Mapping for Distributed Code
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Solution Overview
Problem
Large computer systems struggle with processing divergent and distributed software code files that are siloed and stored across various locations, making it difficult to create a cohesive software application due to the lack of communication and integration between these disparate data sources.
Innovation Solution
A mapping system that generates a graph of relationships between software code files, user identifiers, and revision history, allowing for efficient querying and integration of distributed code by storing location metadata and user identifiers separately from the code content, and using a graph to provide responses to queries.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If software code files are stored separately at individual user devices, then data independence and distribution are improved, but integration difficulty and communication between data sources deteriorate
Solution Approach 1:
The patent introduces a mapping system as an intermediary that sits between distributed code files and the software application creation process. This system automatically generates graphs that map relationships between code files, locations, users, and revisions, enabling integration without requiring the distributed files themselves to communicate. The graph structure serves as the mediator that translates disparate data sources into a unified view.
Solution Approach 2:
The patent segments the code file metadata into distinct components: location metadata, user identifiers, and revision history. These segments are stored separately from the code content itself, allowing the code files to remain distributed and independent while the mapping system creates integrated views through graph structures. This segmentation enables both distribution and integration to coexist.
2Productivity
If location metadata and user identifiers are stored separately from code content, then data organization and query efficiency are improved, but data retrieval complexity deteriorates
Solution Approach 1:
The patent merges separate metadata components (location, user identifiers, revision history) with the code content through the graph data store. While the metadata is technically stored separately, the graph structure combines all these elements into an interconnected representation where queries can efficiently traverse relationships between code files, locations, users, and revisions. This merging approach improves query efficiency by providing direct navigation paths.
Solution Approach 2:
The patent adds a relational dimension to the data storage structure by introducing graph connections between metadata components. Instead of storing metadata in isolated tables or files, the system creates multi-dimensional relationships through graph edges that link code files to locations, users, and revisions. This dimensional expansion enables efficient querying across multiple data types simultaneously.
3Measurement precision
If a graph mapping system is generated, then query response accuracy is improved, but system complexity and processing time deteriorates
Solution Approach 1:
The patent performs preliminary action by automatically generating the graph mapping structure when code files are first ingested or modified. The graph is built in advance with all necessary relationships between code files, locations, users, and revisions pre-established. This preliminary graph generation eliminates the need for complex real-time queries during software application creation, as the mapping information is already available in the graph data store.
Solution Approach 2:
The mapping system is designed to be self-service by automatically generating and updating the graph structure without requiring manual intervention. When code files are added or modified, the system autonomously processes the changes, updates the graph, and makes the updated mapping available for queries. This self-service capability reduces the operational complexity of maintaining the mapping system.
Data Source
AI summary
Systems and methods are provided for implementing an improve mapping process to help identify disparate information associated with a software application in separately stored files. In this way, the information may remain separate and distinct, often times assigned to different teams, devices, and locations, and still be used to create a software application from the disparate information. For example, the system can generate a graph that comprises nodes that identify various information/functions from disparate data sources and edges that identify relationships between this information. Using the graph, the system may receive a query from a user device and generate a response to the query, where the graph can help narrow the search space in determining the response to the query.