AI4PLE: A Methodology for Integrating AI into Product Line Engineering· 将 AI 整合到产品线工程的方法
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
提出 AI4PLE 框架，将人工智能整合到产品线工程中。
- 核心方法
- 通过设计和实现 AI4PLE 方法论框架，利用 AI 技术来支持产品线工程中的关键决策过程，包括特征分析、变异性建模和配置优化等。
- 适合谁读
- 适合研究者和工程师阅读，特别是对 AI 和产品线工程感兴趣的读者。
- 要解决的问题
- 产品线工程中的复用开发面临复杂决策问题，如特征选择、变异性管理和配置优化等，这些问题尚未得到有效解决。
- 关键实验
- 未提供
- 主要贡献
- 首次系统地提出将 AI 集成到产品线工程中的方法，为解决复杂决策问题提供了新的思路和工具。
- 意义与局限
- 该框架有望显著提高产品线工程的效率和质量，推动软件工程领域的发展。然而，实际应用中的效果和适应性仍需进一步验证。