Specification-Driven API Task Mapping for Executable Files
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Solution Overview
Problem
Current automation frameworks require manual generation of executable files, which is time-consuming and error-prone, especially in non-uniform environments, leading to increased errors and suboptimal execution.
Innovation Solution
A system that automatically generates executable files based on specification files, using a mapping dictionary to map API functions to tasks, and generates configuration files tailored to node capabilities, reducing manual input and errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual generation of executable files is used, then flexibility in customization is maintained, but time consumption and error rates increase
Solution Approach 1:
The system performs self-service by automatically generating executable files from specification files without requiring manual intervention. The automated generator parses the specification file, maps API functions to tasks, and produces the executable configuration files, eliminating the need for human operators to manually create these files and thereby reducing both time consumption and error rates
Solution Approach 2:
The patent replaces the mechanical manual process of generating executable files with an automated computational system. The specification file serves as a machine-readable definition, and the automated generator uses parsing and code generation mechanisms to transform this specification into executable configuration files, substituting human manual operations with automated mechanical processes
2Productivity
If automated generation is implemented, then time consumption and errors are reduced, but system complexity increases
Solution Approach 1:
The system segments the complex task of executable file generation into distinct functional components: parsing the specification file, extracting API function definitions, mapping functions to executable tasks, and generating the final configuration files. This segmentation allows each component to handle a specific aspect of the transformation process independently, making the overall complex system more manageable and maintainable
Solution Approach 2:
The patent introduces an intermediary mapping layer that translates between the high-level specification file format and the executable task format. This intermediary mechanism serves as a bridge, allowing the system to automatically transform specifications into executable files without requiring direct complex interactions between all system components, thereby managing complexity through abstraction
3Reliability
If configuration files are customized for node capabilities, then execution reliability improves, but generation complexity increases
Solution Approach 1:
The system applies local quality by generating configuration files with customized content tailored to the specific capabilities and requirements of each node. The automated generator examines node capability specifications and adjusts the generated executable files accordingly, ensuring that each node receives configuration appropriate to its local characteristics rather than a generic one-size-fits-all approach
Solution Approach 2:
The patent utilizes parameter changes by dynamically adjusting generation parameters based on node capability specifications. The automated generator modifies variables such as resource allocation, configuration settings, and task parameters according to the specific capabilities detected in each node, enabling customized execution reliability without requiring manual reconfiguration for each node type
Data Source
AI summary
Some examples of the present disclosure relate to executing configuration files generated from specification files. In one particular example, a system can receive a specification file defining functions for an application programming interface (API) associated with a software entity. The system can generate a graph identifying keywords and relationships associated with the functions. The system can generate, based on the graph, a mapping dictionary that maps the functions to tasks usable in an executable file associated with the API. The system can generate the executable file including one or more of the tasks based on the mapping dictionary and execute the executable file to perform operations associated with the API and the software entity at a node.