Data Science and System Testing: Lessons Learned from a Four-Part Workshop Series

During fall 2022, Big Data Florida ran a series of four workshops on the intersection of data science and system testing. The first was on “Testing Big Data Systems,” which provided the basis for subsequent meetings. The second event was on “Testing Machine Learning (ML) Models,” the third was on “Testing Artificial Intelligence (AI) Applications,” and the fourth was on “Leveraging AI and ML in Testing.” Participants were an interdisciplinary group drawn from data science, testing (hardware, software, and integrated systems), and interested researchers and professionals. This session summarizes some of the lessons learned from this workshop series. Data scientists explored the role of testing in improving model fidelity, increasing implementation robustness, and supporting trustworthy and verifiable systems. Testers discussed the meaning of testing – and being a tester – in the context of big data systems. In this session, attendees will learn about how the interplay between these two important topics promises to significantly affect their personal careers and appreciably influence the data science and testing professions.