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Evaluating Impact of AI Tools in Software Development
This chapter examines the assessment of AI tools in software development, emphasizing the significance of monitoring metrics like code base growth rate, change set size, and copy-paste detection. It explores the evaluation of developer productivity through qualitative surveys on debugging experiences and speculates on the future evolution of developers' roles with advancing AI models. The discussion highlights challenges and opportunities in AI-assisted coding practices, including the impact on Test-Driven Development and code base analysis.