Auto-Generating IoT Test Specs via Activity DSL
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Solution Overview
Problem
The complexity of IoT systems makes manual generation of test specifications cumbersome and untraceable, requiring significant effort and iterations among stakeholders, and lacks support for automatic generation to check the correctness of IoT solutions.
Innovation Solution
A processor-implemented method and system using domain-specific languages (DSL) to receive and analyze data on IoT components, capture solution specifications as activity flows, derive sequences of activities based on guard conditions, and generate test specifications automatically, enabling auto-generation of test specifications for IoT-enabled components.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual generation of test specifications is used for IoT solutions, then deep understanding of domain and implementation details can be utilized, but the process becomes cumbersome, complex, and time-consuming
Solution Approach 1:
The patent introduces an intermediary system that acts as a bridge between the solution specification and test specification generation. This intermediary automatically extracts test requirements from solution specifications using predefined templates and rules, eliminating the need for manual test specification creation while maintaining testing accuracy. The intermediary processes include automated parsing of solution specifications, extraction of testable requirements, and generation of test cases based on predefined templates.
Solution Approach 2:
The patent replaces the mechanical manual process of test specification generation with an automated computational system. The system uses algorithmic processing to parse solution specifications, extract test requirements, and generate test specifications automatically. This substitution eliminates manual effort while maintaining or improving testing quality through consistent application of predefined rules and templates.
2Reliability
If manual generation of test specifications is used, then stakeholder interactions and domain knowledge can be incorporated, but the process requires huge effort and iterations
Solution Approach 1:
The patent changes the parameters of the test specification generation process by introducing automated extraction rules and templates. Instead of manual iteration among stakeholders, the system uses predefined parameters and rules that automatically extract test requirements from solution specifications. This reduces process complexity while maintaining reliability through consistent application of extraction rules and automated validation.
Solution Approach 2:
The patent segments the test specification generation process into distinct automated steps: parsing solution specifications, extracting test requirements, selecting appropriate templates, and generating test cases. Each segment is handled by specific automated rules and algorithms, reducing overall process complexity while ensuring thoroughness and reliability through systematic coverage of all test aspects.
3Ease of operation
If black-box approach is used for generating test specifications, then simplicity is maintained, but it is impossible to generate test specifications for complex IoT systems
Solution Approach 1:
The patent introduces a dynamic approach that adapts the level of automation based on the complexity of the IoT system. For simple systems, the system can operate with higher-level automated generation. For complex systems, it automatically extracts detailed requirements from solution specifications and applies specialized templates. This dynamic adaptation maintains ease of operation while increasing versatility to handle complex IoT architectures, protocols, and interactions.
Solution Approach 2:
The patent creates a universal test specification generation system that can handle multiple types of IoT systems, protocols, and complexities through a single platform. The system uses configurable templates and extraction rules that can be adapted to different IoT domains (smart home, industrial IoT, healthcare IoT, etc.), maintaining ease of operation across diverse applications while achieving versatility through customizable configuration and domain-specific templates.
Data Source
AI summary
This disclosure relates generally to a system and method for auto-generation of test specifications from internet of things (IoT) solution specifications of IoT-enabled components of an IoT network. Testing is the complementary and most important part of any IoT network. Herein, a domain specific language (DSL) is used to specify capability of IoT enabled components. IoT solution specifications are captured from capabilities of IoT enabled components using a predefined activity DSL. A flow of activity is captured to assert transitions among one or more activities based on guard conditions. The flow of activity is analyzed to generate test specifications automatically using a Test Specification DSL based on the asserted transitions. The test specifications are implemented automatically in a predefined target language corresponding to the IoT enabled components.