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When AI codes, Who tests? A teaching case on risk, quality, and governance in LLM-assisted software development
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DOI：10.1016/j.jss.2026.112989.png)
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Abstract
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• This teaching case explores LLM adoption in a software company. • Students investigate recurring bug patterns in AI-generated code. • The case links technical risks to organizational and strategic decisions. • The narrative supports debate on quality, governance, and business value.
Keywords:
Software engineering education
Case-based learning
Large language models (LLMs)
Bug patterns
Software testing
Software quality
Software engineering management
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