SHF: Small: Collaborative Research: Automating the Detection of Architectural Degradation in Software Systems

随着时间的推移，软件系统的体系结构最终会偏离原始设计者的意图，并通过意外引入使原始设计决策无效的更改而降级。体系结构的退化增加了进行新修改的成本，并降低了系统的可靠性--S，直到工程师不再能够有效地发展系统。在这一点上，系统的实际架构可能必须从实现构件中恢复，但这是一个耗时且容易出错的过程，并且留下了未解决的关键问题：架构降级导致的问题很可能会被系统混淆-S许多元素及其相互关系，因此有进一步降级的风险。这个协作项目旨在找出软件系统架构中反映架构降级的位置。拟议的研究包括四项综合研究任务：(1)制定常见退化症状目录。(2)开发一种架构恢复技术，该技术可以自动提取系统的主要构建块以及影响、驱动这些构建块并与其交互的关注点。(3)设计一种技术，用于正式捕获恢复的架构设计决策、它们涉及的关注点以及确定的降级原因。(4)设计一套利用目录自动识别特定于系统的降级实例的技术。因此，这个项目将有可能产生广泛的影响，因为它为软件工程师提供了严格的科学基础，以简化目前昂贵且容易出错的系统维护和发展任务。

Over time, a software system's architecture eventually deviates from the original designer's intent and degrades through unplanned introduction of changes that invalidate original design decisions. Architectural degradation increases the cost of making new modifications and decreases a system?s reliability, until engineers are no longer able to effectively evolve the system. At that point, the system's actual architecture may have to be recovered from the implementation artifacts, but this is a time-consuming and error-prone process, and leaves critical issues unresolved: the problems caused by architectural degradation will likely be obfuscated by the system?s many elements and their interrelationships, thus risking further degradation. This collaborative project aims at pinpointing locations in a software system's architecture that reflect architectural degradation. The proposed research comprises four integrated research tasks: (1) Develop a catalog of commonly occurring symptoms of degradation. (2) Develop an architecture recovery technique that automatically extracts both a system's major building blocks and the concerns that influence, drive, and interact with these building blocks. (3) Devise a technique for formally capturing the recovered architectural design decisions, their involving concerns, and the identified causes of degradation. (4) Devise a suite of techniques that leverage the catalog to automatically identify system-specific instances of degradation. As a result, this project will have a potential for broad impact by providing a rigorous, scientific basis for software engineers to streamline the currently prohibitively expensive and error-prone system maintenance and evolution tasks.