SHF: Small: Collaborative Research: Balancing Expressiveness and Modular Reasoning for Aspect-oriented Programming

SHF：小型：协作研究：平衡面向方面编程的表达性和模块化推理

• 批准号: 1017334
• 负责人: Hridesh Rajan
• 金额: $ 25.77万
• 依托单位: Iowa 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: 2010-08-15 至 2013-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1017334&HistoricalAwards=false
• 关键词: SHF; Small; Collaborative; Research; Balancing

Software systems are poised to keep growing in complexity and permeate deeper into the critical infrastructures of society. The complexity of these systems is exceeding the limits of existing modularization mechanisms and reliability requirements are becoming stringent. Development of new separation of concerns (SoC) techniques is thus vital to make software more reliable and maintainable. Implicit invocation (II) and aspect-oriented (AO) programming languages provide related but distinct mechanisms for separation of concerns. The proposed work encompasses fundamental and practical efforts to improve modularization and reasoning mechanisms for II and AO languages, which is a long standing challenge for both kinds of languages. Addressing these challenges has the potential to significantly improve the quality of software by easing the adoption of new separation of concerns techniques.The project will proceed using the experimental language, Ptolemy, which blends both II and AO ideas. Ptolemy has explicitly announced events, which are defined in interfaces called "event types". Event types help separate concerns and decouple advice from the code it advises. Event type declarations also offer a place to specify advice. The explicit announcement of events allows the possibility of careful reasoning about correctness of Ptolemy programs, since it is possible to reason about parts of the program where there are no events in a conventional manner. The project aims to investigate reasoning by developing a formal specification language and verification technique. The approach is based on the idea of greybox ("model program'') specifications, as found in JML and the refinement calculus. There are known techniques for reasoning about uses of abstractions that have model program specifications, and the project will apply these to Ptolemy. The intellectual merit is in the treatment of expressions in Ptolemy that announce events and those that cause an advice to proceed. A straightforward adaptation of existing reasoning techniques to these cases appears to require a whole program analysis, which is generally not desirable for modular and scalable verification. The project also aims to investigate the utility and effectiveness of Ptolemy and its specification system. A software evolution analysis will be conducted to study the ability of competing aspect-oriented, implicit invocation, and Ptolemy implementations of open source projects to withstand change. Showing Ptolemy's benefits over II and AO languages will help software designers in deciding on advanced mechanisms for separation of concerns.

软件系统的复杂性将不断增长，并更深入地渗透到社会的关键基础设施中。这些系统的复杂性超出了现有模块化机制的限制，可靠性要求也变得越来越严格。因此，开发新的关注点分离 (SoC) 技术对于提高软件的可靠性和可维护性至关重要。隐式调用 (II) 和面向方面 (AO) 编程语言提供了相关但不同的关注点分离机制。拟议的工作包括改进 II 和 AO 语言的模块化和推理机制的基础和实际工作，这对这两种语言来说都是一个长期存在的挑战。解决这些挑战有可能通过简化新的关注点分离技术的采用来显着提高软件质量。该项目将使用实验语言 Ptolemy 继续进行，该语言融合了 II 和 AO 思想。托勒密明确宣布了事件，这些事件在称为“事件类型”的接口中定义。事件类型有助于分离关注点并将建议与其建议的代码分离。事件类型声明还提供了指定建议的位置。事件的明确宣布使得可以仔细推理托勒密程序的正确性，因为可以以传统方式推理程序中没有事件的部分。该项目旨在通过开发正式的规范语言和验证技术来研究推理。该方法基于灰盒（“模型程序”）规范的思想，如 JML 和细化演算中所见。有已知的技术可用于推理具有模型程序规范的抽象的使用，并且该项目将应用这些技术托勒密的智力优点在于对托勒密宣布事件和导致建议继续进行的表达的处理，对这些情况的现有推理技术的直接适应似乎需要整个程序分析，这对于模块化来说通常是不可取的。且可扩展该项目还旨在研究 Ptolemy 及其规范系统的实用性和有效性，以研究开源项目的面向方面、隐式调用和 Ptolemy 实现的竞争能力。展示 Ptolemy 相对于 II 和 AO 语言的优势将有助于软件设计人员决定关注点分离的高级机制。