提出AI融入产品线工程的方法框架，提升系统复用效率。
AI4PLE: A Methodology for Integrating AI into Product Line Engineering
- 构建AI与产品线工程融合的系统化方法框架
- 通过工业多案例研究验证框架有效性
- 适合从事软件复用与智能开发的工程师
基于复用的开发在复杂系统构建中日益重要，能显著降低成本、提升质量并加速上市。产品线工程（PLE）通过共享资产和能力的高效创建、管理与定制，系统化实现这一潜力。但其涉及特征选择、可变性管理和配置优化等复杂决策，对产品线成功至关重要。尽管前景广阔，人工智能（AI）在PLE流程中的系统性集成尚未充分探索。本文提出一种方法论框架，支持AI在PLE中的系统性整合，并通过工业环境下的多案例研究评估其有效性。
原文摘要 · Abstract (English)
Reuse-based development has become increasingly important in the creation of complex systems, offering significant opportunities to reduce costs, improve quality, and accelerate time-to-market. Product Line Engineering (PLE) provides a systematic approach to realizing this potential by enabling the efficient creation, management, and customization of product families by reusing shared assets and capabilities. PLE involves addressing numerous complex decisions, including feature selection, variability management, and configuration optimization, which are critical to the success of a product line. Despite its promise, the systematic integration of Artificial Intelligence (AI) into PLE processes has not yet been comprehensively explored. In this paper, we propose a methodological framework to support the systematic integration of AI into PLE and evaluate its effectiveness through a multi-case study conducted in an industrial context.
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