A scoping review and empirical analysis produce a six-category taxonomy of factors driving AI non-development and abandonment, showing that practical issues like resource limits and organizational dynamics often outweigh ethical concerns in real decisions.
Navigating the Complexity of Generative AI Adoption in Software Engineering
5 Pith papers cite this work, alongside 142 external citations. Polarity classification is still indexing.
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Preference-based prompting raises LLM adherence to object-oriented design principles in UML generation but leaves substantial output variance and model-specific differences intact.
Organizational policies constrain agency in AI-mediated software engineering more than individual preferences, with seniors using detailed delegation and pre-AI instincts while juniors oscillate between over-reliance and avoidance.
UTAUT is suitable for studying individual barriers to GenAI use in software engineering when combined with Bayesian analysis, with three priorities for future research on construct refinement, operationalization, and statistical methods.
The paper describes ongoing efforts to characterize developer diversity in cognition and context and to use personalization to make LLM-based conversational programming assistants more inclusive.
citing papers explorer
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To Build or Not to Build? Factors that Lead to Non-Development or Abandonment of AI Systems
A scoping review and empirical analysis produce a six-category taxonomy of factors driving AI non-development and abandonment, showing that practical issues like resource limits and organizational dynamics often outweigh ethical concerns in real decisions.
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Reliability of Large Language Models for Design Synthesis: An Empirical Study of Variance, Prompt Sensitivity, and Method Scaffolding
Preference-based prompting raises LLM adherence to object-oriented design principles in UML generation but leaves substantial output variance and model-specific differences intact.
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From Junior to Senior: Allocating Agency and Navigating Professional Growth in Agentic AI-Mediated Software Engineering
Organizational policies constrain agency in AI-mediated software engineering more than individual preferences, with seniors using detailed delegation and pre-AI instincts while juniors oscillate between over-reliance and avoidance.
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GenAI in Software Engineering: The Role of Technology Acceptance Models
UTAUT is suitable for studying individual barriers to GenAI use in software engineering when combined with Bayesian analysis, with three priorities for future research on construct refinement, operationalization, and statistical methods.
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Personalizing LLM-Based Conversational Programming Assistants
The paper describes ongoing efforts to characterize developer diversity in cognition and context and to use personalization to make LLM-based conversational programming assistants more inclusive.