On the Future of Software Reuse in the Era of AI Native Software Engineering

2025-08-27

AI Summary

This paper addresses the paradigm shift in software engineering induced by generative AI–driven code reuse in the AI-native era, identifying an emerging risk of “cargo-cult development”—superficial imitation without genuine understanding—that undermines software trustworthiness and sustainability. Through conceptual analysis and comparative paradigm examination, it systematically uncovers core challenges in AI-generated code reuse, particularly concerning comprehensibility, maintainability, and accountability. The paper introduces, for the first time, a research agenda for software reuse tailored to AI-native environments, structured around three pillars: (1) trustworthy evaluation frameworks for AI-generated artifacts; (2) human-AI collaborative reuse mechanisms; and (3) sustainable reuse architectures supporting long-term evolution. This agenda provides both theoretical foundations and actionable pathways toward healthy, controllable, and evolvable AI-augmented software development practices.

Technology Category

• Philosophy and Ethics of AI: Safety, Robustness & Trustworthiness
• Natural Language Processing: Code Generation / Program Synthesis from Natural Language
• Humans and AI: Game Design — Procedural Content Generation & Storytelling

Application Category

• Social Networks and Social Media: Generative AI / large language models and their impact on social systems
• Economics, Online Markets and Human Computation: Economic ramifications for generative AI infrastructure and applications
• Search and Retrieval-Augmented AI: Agentic search

Abstract

Software development is currently under a paradigm shift in which artificial intelligence and generative software reuse are taking the center stage in software creation. Earlier opportunistic software reuse practices and organic software development methods are rapidly being replaced by "AI Native" approaches in which developers place their trust on code that has been generated by artificial intelligence. This is leading to a new form of software reuse that is conceptually not all that different from cargo cult development. In this paper we discuss the implications of AI-assisted generative software reuse, bring forth relevant questions, and define a research agenda for tackling the central issues associated with this emerging approach.

Problem

• Examining implications of AI-assisted generative software reuse
• Addressing cargo cult development risks in AI-native engineering
• Defining research agenda for AI-generated code challenges

Innovation

• AI Native software engineering approach
• Generative software reuse paradigm
• Research agenda for AI-assisted development