GUI for Recursive Complex Data Object Parsing
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Solution Overview
Problem
Parsing and storing markup language documents, such as XML, is a challenging and error-prone task that requires manual coding of parsers, especially when dealing with complex data objects and varying structured formats like REST or SOAP interface calls.
Innovation Solution
A graphical user interface (GUI) based mechanism for defining complex data objects and their relations to tag paths within markup language documents, allowing users to automatically convert paths to a tree structure and vice versa, reducing the need for manual parser coding and simplifying the process of processing markup languages like XML, JSON, and YAML.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual coding of parsers is used to parse markup language documents, then parsing accuracy and reliability are improved, but development time and complexity increase significantly
Solution Approach 1:
The system enables self-service parsing configuration where the markup language document structure automatically defines the parser behavior. The parser reads the markup document, identifies tag paths and data structures, and generates the parsing logic automatically, eliminating the need for manual parser coding while maintaining accuracy through the document's own structural definitions.
Solution Approach 2:
The system performs preliminary analysis of the markup language document structure before actual parsing operations. By pre-defining tag paths, data object mappings, and parsing rules based on the document's own structure, the system prepares the parsing configuration in advance, reducing the time needed for actual parsing operations and eliminating repeated manual coding.
2Reliability
If manual coding of parsers is used to handle complex data objects, then handling reliability is improved, but device complexity and coding effort increase
Solution Approach 1:
The system allows the markup language document to define its own parsing structure automatically. The parser extracts data objects, their relationships, and structural definitions directly from the markup document itself, eliminating the need for manual coding of complex parsing logic while maintaining reliability through the document's inherent structural integrity.
Solution Approach 2:
The system creates a structural model or data object representation that copies the markup language document's hierarchy and relationships. This copied structure serves as the basis for parsing operations, allowing complex data objects to be handled reliably through automated structure replication rather than manual coding.
3Loss of time
If automated parser generation is used, then development time is reduced, but adaptability to different markup formats decreases
Solution Approach 1:
The system performs preliminary structure analysis on each markup language document to automatically generate format-specific parsing configurations. By analyzing the unique structure of each document type beforehand, the system creates tailored parsers that adapt to different formats (XML, JSON, YAML, REST, SOAP) while maintaining automated generation benefits, thus preserving both time efficiency and format adaptability.
Solution Approach 2:
The parser system is designed to be dynamic and adaptable, automatically adjusting its parsing logic based on the input markup language format. The system can dynamically generate parsing configurations for different data formats (XML, JSON, YAML, REST, SOAP) without requiring manual reconfiguration, enabling both rapid customization and high format adaptability through automated structure detection and configuration generation.
4Measurement precision
If manual parser coding is used for each markup language format, then format-specific accuracy is improved, but productivity and efficiency decrease
Solution Approach 1:
The parser system is designed with universal capabilities to handle multiple markup language formats (XML, JSON, YAML, REST, SOAP) through a single automated configuration process. The system can automatically generate format-specific parsing logic while using a unified underlying architecture, thereby maintaining high parsing precision for each format while significantly improving productivity by eliminating the need for separate manual parser development for each format.
Data Source
AI summary
A computational instance of a remote network management platform may include persistent storage and one or more processors. The persistent storage may contain a recursively-defined complex data object, and one or more processors may be configured to: (i) transmit a depiction of a graphical user interface including a visual representation of the recursively-defined complex data object, where the complex data object as well as each array and object therein is represented as a collapsible menu item that can either display or hide its elements; (ii) receive a modification to an element of the complex data object, wherein the modification is either removal of the element, addition of the element, or a change to the associated type of the element; (iii) update the persistent storage to represent the complex data object as modified; and (iv) transmit an update to the visual representation that reflects the complex data object as modified.