Log-Based Mashup Code Generation Without API Endpoints
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Solution Overview
Problem
Conventional API mashup platforms require manual coding and rely on API endpoints, limiting their applicability to applications without exposed APIs, and incur higher development costs and longer development cycles.
Innovation Solution
A system for generating workflow code for log-based mashups without manual coding, using natural language processing to extract trigger output parameters from log data and displaying user-selectable trigger rules and actions, allowing for end-to-end log-based mashups without API endpoints.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If API-based mashup platforms are used, then functionality integration is achieved, but development time and costs increase due to manual coding requirements
Solution Approach 1:
The system enables self-service automated code generation by analyzing log data and automatically creating mashup code without requiring manual programming. The log-based trigger automatically extracts parameters and generates executable code, allowing users to create mashups through configuration rather than coding.
Solution Approach 2:
The system performs preliminary analysis of log data to extract trigger parameters and generate code templates before actual mashup deployment. By pre-processing log data and identifying trigger patterns in advance, the system prepares the foundation for automated code generation, reducing on-demand development time.
2Adaptability or versatility
If API endpoints are required for triggers, then standardized integration is achieved, but applicability is limited to applications without exposed APIs
Solution Approach 1:
The system provides universal trigger capabilities by supporting multiple trigger sources beyond traditional API endpoints. Log-based triggers can monitor various data sources including files, databases, and message queues, making the mashup platform applicable to applications without exposed APIs while maintaining integration reliability through standardized processing.
3Ease of operation
If manual coding is performed, then customization is achieved, but resource consumption increases
Solution Approach 1:
The system replaces manual coding mechanics with automated code generation mechanisms. By substituting human programming effort with algorithmic code synthesis based on log analysis, the system maintains customization capability while significantly reducing computational and human resource consumption associated with manual development.
Data Source
AI summary
According to an aspect of an embodiment, operations include receiving first log data including first information associated with electronic trigger events from a trigger data source. The operations further include extracting trigger output parameters from a first sentence token of the received first log data and displaying a first set of trigger rules onto an electronic User Interface (UI) of a user device based on the extracted trigger output parameters. The operations further include receiving a first input comprising a selection of one or more trigger rules of the displayed first set of trigger rules and receiving a second input comprising a selection of computer-executable actions to be performed based on whether the first information satisfies the one or more trigger rules. The operations further include generating a computer-executable mashup code for execution on a runtime system based on the received first input and the received second input.