🤖 AI Summary
This work addresses the challenge that existing NLP model evaluation metrics struggle to detect behavioral regressions during model updates and lack fine-grained, continuous integration–compatible comparison mechanisms. The study systematically introduces metamorphic testing into NLP model validation, leveraging ten metamorphic relations to automatically generate transformed inputs and analyze behavioral consistency across four consecutive model versions. Applied to three real-world model updates, this approach successfully identified 16 behavioral regressions, 11 of which were critical blocking defects—substantially outperforming conventional evaluation metrics. The proposed method enables effective, automated, and continuous behavioral verification, offering a practical solution for maintaining model reliability throughout iterative development cycles.
📝 Abstract
Evaluating evolving Natural Language Processing (NLP) models is important for ensuring reliable behavior across updates, but standard benchmark metrics do not fully capture how model behavior changes across versions. Existing work has focused mainly on testing models in isolation rather than comparing successive versions in continuous integration workflows. We present Alteron, a tool for detecting behavioral regressions across NLP model versions with metamorphic testing. Alteron constructs a test corpus from labeled source examples and compares model versions on metamorphically transformed inputs. In an evaluation spanning 10 metamorphic relations (MRs), 4 model versions, and 3 model-update transitions, Alteron identified 16 behavioral regressions, 11 of which were release-blocking. The results show that common model updates can preserve overall task performance while still introducing undesirable behavior changes, and that behavioral checks across model versions can reveal failures that aggregate benchmark metrics alone do not capture. The tool is open-source and available at https://github.com/shazzad5709/alteron. A screencast demonstration is available at https://youtu.be/szwiWW5O4do.