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

随着时间的推移，软件系统架构最终偏离了最初的设计者的意图，并通过无计划的引入使最初的设计决策无效的更改而降级。架构退化增加了进行新修改的成本，降低了系统的可靠性，直到工程师不再能够有效地改进系统。在这一点上，系统的实际架构可能必须从实现工件中恢复，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：由架构退化引起的问题可能会被系统的许多元素及其相互关系所混淆，从而有进一步退化的风险。这个合作项目的目的是在精确定位的位置，在软件系统架构，反映架构退化。建议的研究包括四个综合的研究任务：（1）制定一个目录的常见症状的退化。(2)开发一种体系结构恢复技术，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之交互的问题。(3)设计一种技术来正式捕获恢复的架构设计决策、其涉及的问题以及已识别的退化原因。(4)设计一套技术，利用目录自动识别系统特定的降级实例。 因此，该项目将通过为软件工程师提供严格的科学基础来简化目前昂贵且容易出错的系统维护和进化任务，从而产生广泛的影响。

Over time, software systems architecture eventually deviates from the original designers intent and degrades through unplanned introduction of changes that invalidate original design decisions. Architectural degradation increases the cost of making new modifications and decreases systems reliability, until engineers are no longer able to effectively evolve the system. At that point, the systems 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 systems many elements and their interrelationships, thus risking further degradation. This collaborative project aims at pinpointing locations in software systems 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 systems 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.