Autonomous Functional Agents for System Verification
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Solution Overview
Problem
Current methods for testing computing systems for functional correctness fail to simulate the interaction of multiple users and functional agents, particularly in systems with varying user experiences and crowd interactions, leading to incomplete verification of system behavior.
Innovation Solution
A system comprising a system controller, agent repository, and state module that launches autonomous functional agents to interact with the system under test, allowing users to control behavior, define test conditions, and capture output for comparison against expected behavior, enabling comprehensive functional testing of systems with multiple agents.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple autonomous functional agents are launched to simulate crowd interactions, then the comprehensiveness of system verification is improved, but the device complexity increases
Solution Approach 1:
The testing system is segmented into distinct functional components: system controller, agent repository, state module, and multiple autonomous functional agents. Each agent operates independently to simulate specific user behaviors, allowing comprehensive system verification while maintaining manageable complexity through modular design.
Solution Approach 2:
Multiple autonomous functional agents are created as virtual copies of users to simulate crowd interactions. These software-based agents replicate human user behaviors without requiring physical test environments, enabling thorough verification while avoiding the complexity of coordinating actual multiple users.
2Measurement precision
If functional agents simulate varying user experiences and crowd interactions, then the measurement precision of system behavior is improved, but the difficulty of detecting and measuring increases
Solution Approach 1:
The state module continuously monitors and detects the functional state of the system under test by analyzing outputs from multiple autonomous agents. This feedback mechanism compares actual system behavior against expected behavior, enabling precise measurement of system responses to varied user experiences while automating the detection process to reduce measurement difficulty.
Solution Approach 2:
The state module acts as an intermediary between the autonomous functional agents and the system under test. It mediates the complex interactions by standardizing the detection and measurement of functional states, translating diverse agent behaviors into measurable system responses that can be systematically analyzed.
Data Source
AI summary
Example implementations relate to determining a functional state of a system under test. For example, a system to determine a functional state of a system under test may include a system controller to execute a functional test of the system under test by invoking a subset of a plurality of functional agents to interact with the system under test. Further, the system may include an agent repository to interact with the system controller and store the plurality of functional agents. Also, the system may include a state module to determine a functional state for the system under test by querying each of the subset of functional agents and comparing aggregated results from the subset of functional agents against defined for the system under test.