Test Oracle Automation in the Era of LLMs
Facundo Molina, Alessandra Gorla, Marcelo d’Amorim
Abstract
The effectiveness of a test suite in detecting faults highly depends on the quality of its test oracles. Large Language Models (LLMs) have demonstrated remarkable proficiency in tackling diverse software testing tasks. This article aims to present a roadmap for future research on the use of LLMs for test oracle automation. We discuss the progress made in the field of test oracle automation before the introduction of LLMs, identifying the main limitations and weaknesses of existing techniques. Additionally, we discuss recent studies on the use of LLMs for this task, highlighting the main challenges that arise from their use, e.g., how to assess quality and usefulness of the generated oracles. We conclude with a discussion about the directions and opportunities for future research on LLM-based oracle automation.