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Research:Question-38-AI-Development-Quality-Impact
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=== Current Quality Assessment Challenges === Evaluating AI impact on software quality faces several methodological challenges: '''Temporal Complexity:''' Quality impacts may manifest over different timeframes, with immediate benefits potentially masking longer-term costs. '''Context Sensitivity:''' Quality impacts likely vary significantly based on project characteristics, team capabilities, and AI tool implementation approaches. '''Measurement Limitations:''' Traditional quality metrics may not capture all relevant aspects of AI impact on software engineering outcomes. '''Confounding Variables:''' Multiple factors affect software quality, making it challenging to isolate AI-specific impacts.
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