SHF: Small: Scenario-Based Validation of Design Models

SHF：小型：基于场景的设计模型验证

• 批准号: 1018711
• 负责人: Indrakshi Ray
• 金额: $ 49.99万
• 依托单位: Colorado State University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-08-01 至 2015-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1018711&HistoricalAwards=false
• 关键词: SHF; Small; Scenario; Based; Validation

Developing complex software systems that play critical roles in organizations and societies is currently labour intensive and costly. There is a need for research on the means to significantly reduce the cost and effort of developing complex software systems. Model driven engineering (MDE) research is primarily concerned with reducing software development costs through the use of technologies that support rigorous analysis of software models and automated transformation of verified models to dependable implementations. Complexity is tackled through (1) the use of models that describe complex systems at multiple levels of abstraction and from a variety of perspectives, and (2) automated support for transforming and analyzing models. Software developers use multi-modeling notations such as the Unified Modeling Language (UML) to manage design complexity. A challenge in using multi-models is ensuring that structural and behavioral properties are consistently described across the different models. The highly iterative nature of software design makes manual consistency checking of multi-models tedious and error prone. Furthermore, iterative, incremental development of models requires support for analyzing incomplete models. While heavyweight formal analysis techniques are useful for analyzing detailed, complete design models of highly-critical systems, lightweight analysis techniques that allow developers to do ``just enough'' analysis with available information are needed to support iterative, incremental software development. The primary aim of this project is to develop a lightweight consistency analysis method that supports iterative, incremental development of software design multi-models.The research aims to produce an analysis method that provides modelers with meaningful feedback on the consistency of UML design multi-models as they evolve in an iterative and incremental process. The scenario-based UML design analysis method that will be developed extends the applicability of existing UML static analysis tools such as USE and OCLE to the analysis of behavior. The approach will allow developers to automatically check a design multi-model against a set of scenarios describing desirable and undesirable behaviors. What will make this analysis method different from other rigorous analysis methods is its tolerance for incompleteness. Specifically, the research aims to produce a method that will provide useful feedback on consistency when only partial descriptions of behavior are provided in multi-models. In addition to the above, the static analysis method will be integrated with a dynamic analysis tool called UMLAnT that allows developers to animate scenarios captured by UML class models. The support for both static and dynamic model analysis and the ability to analyze incomplete models can significantly reduce the cost and effort currently associated with producing dependable implementations from models in iterative, incremental design processes.

开发在组织和社会中发挥关键作用的复杂软件系统目前是劳动密集型和费用高昂的。需要研究显著降低开发复杂软件系统的成本和工作量的方法。模型驱动工程(MDE)研究主要关注通过使用支持软件模型的严格分析和验证模型到可靠实现的自动转换的技术来降低软件开发成本。复杂性是通过(1)使用在多个抽象级别和从不同角度描述复杂系统的模型来解决的，以及(2)对模型转换和分析的自动化支持。软件开发人员使用多种建模符号(如统一建模语言(UML))来管理设计复杂性。使用多模型的一个挑战是确保跨不同模型一致地描述结构和行为属性。软件设计的高度迭代性质使得手动检查多模型的一致性变得单调乏味且容易出错。此外，模型的迭代、增量开发需要支持分析不完整的模型。虽然重量级形式分析技术对于分析高度关键系统的详细、完整的设计模型很有用，但需要轻量级分析技术来支持迭代的、增量的软件开发，这种技术允许开发人员利用可用的信息进行“恰到好处”的分析。该项目的主要目的是开发一种支持软件设计多模型迭代、增量开发的轻量级一致性分析方法。该研究旨在产生一种分析方法，该方法能够在软件设计多模型在迭代和增量过程中演化时为建模者提供有意义的反馈。即将开发的基于场景的UML设计分析方法将现有的Use和Ocle等UML静态分析工具的适用性扩展到行为分析。该方法将允许开发人员根据一组描述期望和不期望行为的场景自动检查设计多模型。这种分析方法与其他严格分析方法的不同之处在于它对不完备性的容忍度。具体地说，这项研究旨在产生一种方法，当在多个模型中仅提供对行为的部分描述时，该方法将提供关于一致性的有用反馈。除此之外，静态分析方法还将与一个名为UMLAnT的动态分析工具相集成，该工具允许开发人员对由UML类模型捕获的场景进行动画处理。对静态和动态模型分析的支持以及分析不完整模型的能力可以显著降低当前与迭代、增量设计过程中从模型生成可靠实现相关的成本和工作量。