Abstract
Large Language Models (LLMs) are increasingly integrated into software applications. Downstream application developers often access LLMs through APIs provided as a service. However, LLM APIs are often updated silently and scheduled to be deprecated, forcing users to continuously adapt to evolving models. This can cause performance regression and affect prompt design choices, as evidenced by our case study on toxicity detection. Based on our case study, we emphasize the need for and re-examine the concept of regression testing for evolving LLM APIs. We argue that regression testing LLMs requires fundamental changes to traditional testing approaches, due to different correctness notions, prompting brittleness, and non-determinism in LLM APIs.
| Original language | English |
|---|---|
| Title of host publication | Proceedings - 2024 IEEE/ACM 3rd International Conference on AI Engineering - Software Engineering for AI, CAIN 2024 |
| Publisher | Association for Computing Machinery, Inc |
| Pages | 166-171 |
| Number of pages | 6 |
| ISBN (Electronic) | 9798400705915 |
| DOIs | |
| Publication status | Published - 14 Apr 2024 |
| Externally published | Yes |
| Event | 3rd International Conference on AI Engineering, CAIN 2024, co-located with the 46th International Conference on Software Engineering, ICSE 2024 - Lisbon, Portugal Duration: 14 Apr 2024 → 15 Apr 2024 |
Publication series
| Name | Proceedings - 2024 IEEE/ACM 3rd International Conference on AI Engineering - Software Engineering for AI, CAIN 2024 |
|---|
Conference
| Conference | 3rd International Conference on AI Engineering, CAIN 2024, co-located with the 46th International Conference on Software Engineering, ICSE 2024 |
|---|---|
| Country/Territory | Portugal |
| City | Lisbon |
| Period | 14/04/24 → 15/04/24 |
Bibliographical note
Publisher Copyright:© 2024 Copyright is held by the owner/author(s). Publication rights licensed to ACM.
Keywords
- large language models (LLM)
- regression testing
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