Year: 2025
Type: conference-paper
Abstract: Generative Artificial Intelligence (GenAI) is transforming software development processes, including test and evaluation (T&E). From automating test case design to enabling continuous testing in DevOps pipelines, AI-driven tools enhance the efficiency, accuracy, and speed of software testing. At the same time, the integration of AI components into software-reliant systems introduces new challenges for verification and validation (V&V). Traditional T&E methodologies must evolve to address issues such as AI bias, hallucinated outputs, and the complexity of validating non-deterministic behaviors. This position paper examines how existing T&E methods must evolve to account for AI's stochastic nature, and conversely how GenAI is transforming T&E practices across the software development lifecycle (SDLC).
Authors: Laura Freeman, John Robert, Heather Wojton
Language: English
Subfield: Software
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
OpenAlex ID: W4412704012