API-Driven Continuous Testing Platform for Unified Report Normalization
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Solution Overview
Problem
Current testing frameworks for software on enterprise networks require multiple frameworks for different types of tests and application architectures, leading to disparate report formats that complicate aggregation, storage, and analysis, and necessitate manual conversion for Continuous Integration, Continuous Delivery, and Continuous Testing (CI/CD) pipelines, resulting in inefficiencies and data inaccuracies.
Innovation Solution
An API-driven continuous testing platform with a test engine and agents that inspect various software applications, generating uniform reports and integrating with CI/CD pipelines to automate test results processing and code updates, allowing for a single platform to handle all types of testing across different applications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple test frameworks are used for different types of tests and application architectures, then testing coverage and specialization are improved, but report format disparity and system complexity increase
Solution Approach 1:
The patent introduces an intermediary layer (report normalization service) that sits between multiple test frameworks and the central reporting system. This intermediary automatically converts disparate report formats from different test frameworks into a unified standard format, allowing the system to maintain multiple specialized test frameworks while presenting a single unified interface for report aggregation and analysis.
Solution Approach 2:
The patent creates a universal reporting platform that can handle reports from multiple different test frameworks through a single unified interface. The system implements multi-functionality by enabling one central reporting system to process, normalize, and analyze reports from various test frameworks (performance testing, functional testing, security testing, etc.) without requiring separate reporting infrastructures for each framework.
2Adaptability or versatility
If multiple test frameworks generate reports in different formats, then specialized testing capabilities are maintained, but aggregation and storage efficiency deteriorate
Solution Approach 1:
The report normalization service acts as an intermediary that automatically transforms reports from various test frameworks into a unified format before storage. This intermediary layer handles format conversion, field mapping, and data standardization, enabling efficient aggregation of reports from multiple sources without manual intervention and maintaining specialized testing capabilities across different frameworks.
3Measurement precision
If manual conversion of test results is performed for CI/CD pipelines, then data accuracy can be verified, but time consumption and error susceptibility increase
Solution Approach 1:
The system implements self-service automation where the report normalization service automatically performs format conversion, validation, and CI/CD pipeline integration without manual intervention. The automated processes include self-validation of converted data, self-correction of formatting issues, and self-integration with CI/CD pipelines, eliminating manual conversion steps while maintaining data accuracy through built-in validation rules and error handling mechanisms.
4Productivity
If multiple testing frameworks are integrated into a single CI/CD pipeline, then workflow consolidation is improved, but integration complexity and data consistency challenges increase
Solution Approach 1:
The patent applies homogeneity by enforcing a unified report format and data structure across all test frameworks integrated into the CI/CD pipeline. The normalization service ensures that all reports conform to the same schema, use consistent field names, and follow uniform formatting rules, thereby simplifying integration complexity while enabling workflow consolidation of multiple testing frameworks into a single pipeline.
Data Source
AI summary
A system for providing an API-driven continuous test platform is disclosed. The system may include one or more processors, a test engine, one or more test agents, and a database. The system may prepare (according to a configuration file) a first test configuration comprising a first selection of the one or more test agents, execute (using the test engine) the first test configuration to produce one or more first test results, and store (using the database) the one or more first test results. Finally, the system may process (using a continuous integration and continuous delivery (CI/CD) pipeline) the first test results by performing at least one of the following CI/CD processes: updating a central code base of an enterprise production environment, rejecting at least one code snippet processed by the test engine during execution of the first test configuration, and marking the first test results as inconclusive.