SoD: A Generative Model of Feature Interactions

SoD：特征交互的生成模型

• 批准号: 0438786
• 负责人: Don Batory
• 金额: $ 41.47万
• 依托单位: University of Texas at Austin
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-12-15 至 2008-11-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0438786&HistoricalAwards=false
• 关键词: SoD; Generative; Model; Feature; Interactions

0438786Don BatoryU of Texas AustinA Generative Model of Feature InteractionsThis research extends work in the area of Generative Programming, which explains how programs in a domain are designed from features. A generative programming model is both constructive and predictive because it tells us how to synthesize programs in a domain with particular properties. A program's design can be specified as a base program plus a set of features, which are units of program functionality. Programs consisting of features can be formalized mathematically as an algebra with suitable composition operators. Research in generative programming shows that evaluation of algebraic expressions synthesizes the target program, and expression optimization optimizes the program's design. Feature interaction occurs when one or more features modify or influence another feature. We focus on interactions that are static and structural: how a feature influences (or changes) the source code of another feature. Our research contributes to a Science of Design by showing how feature interactions obey algebraic laws that lead to highly structured programs that are amenable to synthesis, optimization, and evolution. We will demonstrate practical applications of our work: (1) refactoring Java legacy applications into feature-based designs (so that features can be more easily added and removed), and (2) realizing a form of on-demand modularization, where a query specifies a particular concern and our theory tells us how to extract software that satisfies that query.

0438786Don BatoryU of Texas Austin特征交互的生成模型这项研究扩展了生成编程领域的工作，它解释了域中的程序是如何从特征设计的。生成式编程模型既具有建设性又具有预测性，因为它告诉我们如何在具有特定属性的域中合成程序。一个程序的设计可以被指定为一个基本程序加上一组功能，这些功能是程序功能的单元。由特征组成的程序可以在数学上形式化为具有合适的复合运算符的代数。对生成式编程的研究表明，代数表达式的求值可以综合目标程序，表达式优化可以优化程序的设计。当一个或多个特征修改或影响另一个特征时，就会发生特征交互。我们专注于静态和结构化的交互：一个功能如何影响（或改变）另一个功能的源代码。我们的研究有助于设计科学，展示了功能交互如何遵守代数定律，导致高度结构化的程序，适合合成，优化和进化。我们将展示我们工作的实际应用：（1）将Java遗留应用程序重构为基于功能的设计（以便更容易添加和删除功能），以及（2）实现一种按需模块化形式，其中查询指定特定的关注点，我们的理论告诉我们如何提取满足该查询的软件。