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Isolating Noisy Labelled Test Cases in Human-in-the-Loop Oracle Learning
Charaka Geethal Kapugama
https://arxiv.org/abs/2506.13273 https://

Isolating Noisy Labelled Test Cases in Human-in-the-Loop Oracle Learning
Incorrectly labelled test cases can adversely affect the training process of human-in-the-loop oracle learning tech-niques. This paper introduces ISONOISE, a technique designed to identify such mislabelled test cases introduced during human-in-the-loop oracle learning. This technique can be applied to programs taking numeric inputs. Given a compromised automatic test oracle and its training test suite, ISONOISE first isolates thetest cases suspected of being mislabelled. This task is performed …