Predictive Data Structure for Offline Application Execution
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Solution Overview
Problem
Network connectivity issues cause online applications to fail when clients lose connection with servers, leading to incomplete transactions and loss of functionality, as cached data may be outdated or unavailable due to security concerns, preventing scripts and HTML from executing offline.
Innovation Solution
A predictive data structure is generated to allow offline applications to continue executing by determining exit points in source code, identifying conditional statements, and creating data structures to replace server requests, enabling the application to continue along its execution path as if network connected.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the application caches the requested resource to enable offline operation, then the application can continue to function when the network is unavailable, but the cached data may be outdated and produce incorrect results
Solution Approach 1:
The system performs preliminary actions by generating predictive data structures in advance that anticipate the data the application will need offline. Instead of simply caching static resources, the system pre-generates predictive representations of server responses based on the application's execution path and conditional statements, ensuring accurate data is available before network connectivity is lost.
Solution Approach 2:
The system creates a predictive copy of the server's data structure that mirrors what the server would return. This predictive data structure is a local copy generated from analyzing the application code and predicted execution paths, allowing the application to operate offline with accurate data that replicates the server's response without being limited to static cached versions.
2Productivity
If the application operates offline without server connection, then the application can maintain functionality during network outages, but scripts and HTML cannot execute because they require server calls
Solution Approach 1:
The predictive data structure acts as an intermediary between the application code and the server. Instead of requiring direct server calls for every script execution, the system creates a local predictive representation that mediates data access, allowing scripts to execute offline by querying the predictive structure rather than making network requests.
Solution Approach 2:
The system enables the application to serve itself offline by generating predictive data structures locally from the application's own code analysis. The application becomes self-sufficient by creating its own data representations without continuous server assistance, allowing full script execution capability during network outages.
3Reliability
If the application uses cached data for offline operation, then the application can run without network connection, but security or privacy concerns may prevent caching
Solution Approach 1:
The system extracts only the essential predictive data structure information needed for offline operation, removing unnecessary sensitive data from the caching process. By generating minimal predictive representations based on code analysis rather than caching complete server responses, the system reduces security risks while maintaining offline functionality.
Data Source
AI summary
A method, apparatus, and/or computer program product generates a predictive data structure for an application when operating offline in a network connected data processing system, the application comprising source code having an execution path. The method comprises: determining an exit point within the source code of the application; determining, from the exit point, an execution path comprising at least one conditional statement; identifying one or more branches of the at least one identified conditional statement and for each identified branch determining an expected response; for each determined expected response, generating a data structure from the response; continuing along the execution path of the source code from the exit point and replacing each request for a resource in the source code with a pointer to the generated data structure; and executing the source code with the pointer to the generated data structure from the determined exit point.