Analytical Design of Evolutionary Control Flow Components

The market demands that software systems be adaptable to changes in requirements. Software must be evolvable to solve slightly different problems over time. The transition from real-world requirements to software is a human-intensive and potentially complex process that provides limited automated support for the analysis of alternative designs with respect to their evolvability. In this paper, we propose an analytical software design approach to localize changes to control flow requirements. We present an analytical and “heuristically good” design approach to generate control components that localize change and reduce the computational complexity of an optimal approach. We apply our heuristic to an example and summarize the results. Lastly, we propose future research and summarize our ideas.</p

The Metaphor Project Summary Report: Technology for Analyzing Change and Composing Reusable, Real-Time Components and Applications

There is an increasing need for software systems to adaptively support changes in application-level objectives [Fayad96]. Real-time software evolution involves changes in software structure and meaning over time to satisfy changes in application requirements. The problem is that the process of changing real-time software often involves extensive impact of change (non-localized change) and substantial manual effort. The process can be costly and error-prone. The Metaphor Project hypothesis was that a systematic approach to thinking about change used with an analytical method for “localizing” software solution features that would be impacted by the same changes can result in a significant reduction in the effort needed to modify these solutions over time. The proposed work was the research and development of a model for organizing information about change, of algorithms to systematically and automatically localize change to basic solution features such as data/operations and control flow, and of a process for analyzing the basic features with respect to change and reuse. This report summarizes the Metaphor Project objectives, accomplishments, and technical as well as educational contributions.</p

An Analytical Approach to Change for the Design of Reusable Real-Time Software

In this paper, we present an analytical method for incorporating knowledge about change into the design of reusable real-time software components. We apply this method to the construction of algorithmic software solutions that minimize the effect of anticipated changes in the solution. The motivation for our research is based on two premises: (1) software solutions that can easily be adapted to changes in the problem and solution domains are more readily reused and (2) the reuse of reliable software promotes the construction of high quality software systems and reduces development costs. This paper also briefly overviews our current research goals involving analysis and design methods to enable software engineers to rapidly adapt their real-time software solutions to changing application requirements.</p

The Amaranth Framework: Probabilistic, Utility-Based Quality of Service Management for High-Assurance Computing

System resource management for high-assurance applications such as the command and control of a battle group is a complex problem. These applications often require guaranteed computing services that must satisfy both hard and soft deadlines. In addition, their resource demands can vary significantly over time with bursts of high activity amidst periods of inactivity. A traditional solution has been to dedicate resources to critical application tasks and to share resources among noncritical tasks. With the increasing complexity of high-assurance applications and the need to reduce system costs, dedicating resources is not a satisfactory solution. The Amaranth Project at Carnegie Mellon is researching and developing a framework for allocating shared resources to support multiple quality of service (QoS) dimensions and to provide probabilistic assurances of service. This paper is an overview of the Amaranth framework, the current results from applying the framework, and the future research directions for the Amaranth project.</p