Context Data Structures for Business Event Resolution
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Solution Overview
Problem
Efficiently managing and resolving numerous business events from diverse sources in computing systems is challenging, leading to poor performance due to extensive communication requirements for gathering necessary information.
Innovation Solution
The implementation of data structures that include context information related to business events, generated using declarative programming languages, which assist in retrieving further information and enable efficient event resolution by encapsulating context details and providing event resolution procedures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional event processing methods are used to gather information from multiple sources, then complete event resolution information can be obtained, but communication overhead increases and performance deteriorates
Solution Approach 1:
The patent applies preliminary action by pre-generating data structures that contain context information about business events before actual event resolution is needed. These data structures are created during system initialization or design time, storing information about event sources, relationships, and resolution procedures. When events occur, the pre-prepared data structures enable immediate access to necessary context without requiring real-time communication to gather information, thus reducing communication overhead while maintaining complete event resolution capability
Solution Approach 2:
The patent introduces data structures as intermediaries between event sources and event resolution processes. These data structures act as mediators that encapsulate context information from multiple event sources in a standardized format. Instead of directly communicating with multiple event sources during resolution, the system queries the intermediary data structures, which have already organized and stored the necessary context information, thereby reducing the communication burden while ensuring complete information retrieval
2Productivity
If data structures include comprehensive context information to assist event resolution, then event processing efficiency improves, but data structure complexity increases
Solution Approach 1:
The patent applies segmentation by dividing the comprehensive context information into modular data structures organized by event type, source, and resolution procedure. Each data structure contains only the specific context information relevant to particular event categories rather than all possible information. This segmentation allows the system to load and process only the necessary data structures for handling specific events, improving processing efficiency while managing complexity through organized modularity
Solution Approach 2:
The patent creates universal data structure templates that can serve multiple event types and resolution scenarios. These standardized templates define common context information fields and relationships that apply across different business events. By using universal templates rather than custom structures for each event type, the system reduces overall complexity while maintaining comprehensive context information availability, as the same data structure framework supports multiple event processing functions
3Adaptability or versatility
If data structures are generated dynamically to include information to assist retrieving further information, then adaptability to different event types improves, but generation time and computational resources increase
Solution Approach 1:
The patent applies preliminary action by pre-defining data structure templates and schemas during system design or initialization phases. These templates include predefined fields, relationships, and retrieval procedures for various event types. When new events arrive, the system instantiates these pre-defined templates rather than generating structures from scratch, significantly reducing generation time while maintaining adaptability to different event types through the flexibility of the template system
Solution Approach 2:
The patent uses copying by creating instances of pre-defined data structure templates for specific events. Instead of generating entirely new data structures for each event type, the system copies and populates standardized templates with event-specific data. This copying approach maintains adaptability across different event types while dramatically reducing the computational resources and time required for data structure generation, as the structural framework is reused across multiple events
Data Source
AI summary
Methods and apparatus, including computer program products, related to data structures for context information related to business events. Data characterizing an event of one or more business processes (e.g., an event corresponding to a business activity in one or more computer-implemented business processes) is received, and a data structure is generated to enable event resolution. The data structure is generated in response to receiving the data and the data structure includes information about the event derived from the data and information to assist retrieving further information related to the event. The data structure may be defined in accordance with a declarative programming language. A business process to include events that are resolved with the use of a data structure including context information and a data structure (e.g., a designtime data structure) may be modeled in a visual modeling tool.