The Impact of Generative AI on Test & Evaluation: Challenges and Opportunities

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).

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Publication Details

Published
2025-06-23
DOI
https://doi.org/10.1145/3696630.3728723
Citations
3
Primary Topic
Explainable Artificial Intelligence (XAI)
Type
article
Field-Weighted Citation Impact
7.44
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article

The Impact of Generative AI on Test & Evaluation: Challenges and Opportunities

Laura Freeman, Heather Wojton, John Robert
3 citations
Explainable Artificial Intelligence (XAI)
7.44
article

The Impact of Generative AI on Test & Evaluation: Challenges and Opportunities

Laura Freeman, Heather Wojton, John Robert
article en
3 citations

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).

Institute For Defense Analyses (US), Computational Diagnostics (United States) (US), Virginia Tech (US)
Openalex Percentile: Top 3%
Explainable Artificial Intelligence (XAI)
7.44
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