2 papers
cs.SE2026
Beyond Rule-Based Mutation Testing: Test-Aware Mutant Generation Using Large Language Models
Nils Kiele, Zainab Saad, Zirui Wang +2
Mutation testing evaluates test-suite adequacy by injecting synthetic faults into program code. However, traditional rule-based tools often generate large numbers of trivial, redun…
cs.CL2024
Learning to Predict Usage Options of Product Reviews with LLM-Generated Labels
Leo Kohlenberg, Leonard Horns, Frederic Sadrieh +7
Annotating large datasets can be challenging. However, crowd-sourcing is often expensive and can lack quality, especially for non-trivial tasks. We propose a method of using LLMs a…