Failure-based Testing: A Testing Paradigm in the Era of Large Language Models
Automatic test generation is an important software engineering task. Various test generation paradigms (e.g., code-coverage-based, model-based) have been proposed. One major objective of these paradigms is to generate test cases that achieve high coverage of a program’s components/functionalities. Despite many advances, there are still two outstanding challenges for these paradigms: 1) high coverage is not necessarily correlated with bug-revealing capabilities, 2) constructing a test oracle is often an undecidable problem. To address these challenges, we plan to study the paradigm of failure-based testing, which focuses on constructing failure-inducing test cases. We observe that LLMs have several desired characteristics, that can address these challenges for finding failure-inducing test cases.
Mon 11 SepDisplayed time zone: Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna change
10:30 - 12:00 | |||
10:30 30mTalk | Early Detection of Defects in Machine Learning Programs by Semi-Static Analysis Doctoral Forum Yiran Wang Linköping University | ||
11:00 30mTalk | Mutation Testing for supporting Smart Contract code inspection Doctoral Forum Morena Barboni University of Camerino | ||
11:30 30mTalk | Failure-based Testing: A Testing Paradigm in the Era of Large Language Models Doctoral Forum Li Tsz On The Hong Kong University of Science and Technology | ||
