Wireless radio frequency applications are complex and have multiple components that interact with each other, sometimes in unexpected ways. The interactions can be complex and therefore, require extensive testing to cover the possible scenarios. Due to the large number of combinations of parameters, it is time consuming to write or modify test scripts manually for each possible combination of parameters when testing such applications. Further, manually writing or modifying test scripts can also introduce bugs. This disclosure describes the use of an artificial intelligence (AI) bot to generate test scripts based on human language inputs provided by a user. The AI bot can be implemented using a large language model (LLM) and can generate new test scripts for any new user input combination of factors, e.g., radio technology, channels, rates, power settings, etc. for wireless radio frequency applications testing. A core repository of existing test scripts and functions is utilized by the LLM. The LLM that automatically generates the test scripts is limited to functions that are part of the repository.
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n/a, "LLM-based Automatic Test Script Generation for Wireless Applications", Technical Disclosure Commons, (August 25, 2023)