Leveraging LLMs for Generation of Unusual Text Inputs in Mobile App Tests: Results and Analysis

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Leveraging LLMs for Generation of Unusual Text Inputs in Mobile App Tests: Results and Analysis
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Using InputBlaster, a novel approach in leveraging LLMs for automated generation of diverse text inputs in mobile app testing.

This paper is under CC 4.0 license.

In detail, for InputBlaster w/o valid Input , we provide the information related to the input widgets to the LLM in Module 2 and set other information from Module 1 as “null”. For InputBlaster w/o enrich Examples , we set the examples from Module 3 as “null” when querying the LLM. Note that, since Module 2 is for generating the unusual inputs which is indispensable for this task, hence we do not experiment with this variant. 5.2.1 Contribution of Modules.

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