Research Initiation Award: Toward Scaling Up: Visual Data Abstraction for Declarative Visual Programming Languages

可视化编程语言(VPL)提供了以更低的劳动力成本获得更高可靠性的希望，但前提是它们可以针对实际规模的编程项目进行扩展。这项研究通过开发一种交互的、可视化的、但功能强大的数据抽象方法，解决了扩展声明性VPL的一个关键因素。视觉方法通过简单性增加了VPL的表现力，而不是以牺牲简单性为代价的传统方法。开发的概念正在研究说明性VPL中实现，并向感兴趣的研究人员提供。这项工作建立在最近在数据抽象、事件处理和扩展问题方面的工作基础上。解决了视觉设计问题，目前的实施正在准备作为基础研究系统。这项研究寻求将可视化和灵活的方法结合到代码重用中。同时，在早期事件工作的基础上，正在开发一种简单的异常处理方法。关于数据抽象方法的视觉影响和视觉支持的更多工作预计将加强结果的简单性和有效性。

Visual programming languages (VPLs) offer the hope of higher reliability at lower labor costs, but only if they can be scaled up for realistically-sized programming projects. This research addresses a critical factor in scaling up declarative VPLs, by developing an interactive and visual yet powerful approach to data abstraction. The visual approach adds expressive power to VPLs through simplicity, rather than the traditional approach of providing them at the expense of simplicity. The concepts developed are being implemented in a research declarative VPL and made available to interested researchers. This work builds upon recent work in data abstraction, event- handling, and the scaling-up problem. Visual design issues are addressed, and the current implementation is being prepared to serve as a base research system. The research seeks the incorporation of a visual and flexible approach to code reuse. At the same time, a simple approach to exception handling based on the earlier work on events is being developed. Additional work regarding visual impact and visual support for the approach to data abstraction is expected to enhance the simplicity and effectiveness of the results.