CAREER: A Mining-Based Approach for Consistent and Timely Adaptation of Component-Based Software

越来越多的人期望软件能够动态地调整其行为，以响应计算基础设施以及周围物理环境中不断变化的条件。软件动态适应的两个重要问题是：(1)如何防止软件在适应过程中出现故障；(2)如何减少软件所提供功能的中断。这项研究将设计一种新的技术，通过自动确定何时是对正在运行的软件系统进行更改的最佳时间来处理这些问题。本研究的原理将为动态自适应软件工程的新方法提供基础。研究的结果将被纳入教育，这样未来的软件工程师就能更好地应对构建适应性软件的挑战。该方法将通过一套开源工具来实现，为将研究成果转化为行业铺平道路。所有先前针对该研究问题的技术都假定了详细的软件组件依赖模型的可用性。这项研究将开发一种新的技术，在这些模型不可用、难以构建或由于软件的发展而过时的情况下解决这个问题。指导这项研究的假设是，通过监控一个软件系统？如果将系统的执行历史（例如，消息交换、方法调用）保存足够长的一段时间，就有可能挖掘出系统组件之间交互和依赖关系的准确模型。该研究将证明以这种方式推断的模型如何用于(1)确保运行软件中的更改不会产生可能危及系统的不一致？(2)控制系统产生的中断程度。(3)自动调整模型以适应不断变化的软件组件之间的依赖关系。

Increasingly, software is expected to dynamically adapt its behavior in response to changing conditions in the computation infrastructure as well as the surrounding physical environment. Two important problems in dynamic adaptation of software are (1) how to prevent failure of the software during adaptation, and (2) how to reduce disruptions in the functionalities provisioned by the software. This research will devise a novel technique for dealing with these problems by automatically determining when is the best time for making changes to a running software system. The principles emerging from this research will provide the foundation for a new method of engineering dynamically adaptive software. The results of the research will be incorporated into education, such that tomorrow's software engineers are better equipped to tackle the challenges of constructing adaptive software. The approach will be realized via a suite of open source tools to pave the way for transitioning the research results to the industry. All prior techniques targeted at this research problem have assumed the availability of detailed software component dependency models. This research will develop a novel technique that solves this problem in settings where such models are either not available, difficult to build, or outdated due to the evolution of the software. The hypothesis guiding this research is that by monitoring a software system?s execution history (e.g., message exchanges, method invocations) for a sufficiently long period of time, it is possible to mine an accurate model of interactions and dependencies among the system's components. The research will demonstrate how models inferred in this way can be used to (1) ensure changes in the running software do not create inconsistencies that could jeopardize the system?s functionality, (2) control the level of disruption incurred in system?s operations due to adaptation, and (3) automatically adjust the models to changing dependencies among the potentially evolving software components.