This paper presents QoS explorer, an interactive tool we have developed which predicts quality of service (QoS) of a workflow from the QoS characteristics of its constituents, even when the relationships involved are complex. This facilitates design and instantiation of workflows to satisfy QoS constraints, as it enables the user to discover and focus effort on the aspects of a workflow which most affect their primary QoS concerns, thus improving efficiency of workflow development. Further, the underlying model we use is more sophisticated than those of similar recent work (Jaeger et al., 2005; Ardagna and Pernici, 2005; Menasce, 2004), and includes processing of entire statistical distributions and probabilistic states (instead of the simple numeric constants used elsewhere) to model such non-constant variables as execution time

Dynamic reconfiguration techniques appear promising for building systems that have requirements for adaptability and/or high availability. Current systems that support dynamic reconfiguration tend to use a single, fixed, reconfiguration algorithm to manage the change process. Furthermore, existing change management systems lack support for measuring the impact of reconfiguration on a running system. In this paper, we introduce OpenRec, an open framework for managing dynamic reconfiguration which addresses these drawbacks. Using OpenRec, developers can observe the costs, in terms of time and disturbance, associated with making a particular run-time change. In addition, OpenRec employs an extensible set of reconfiguration algorithms where one algorithm can be substituted for another. Developers can thus make an informed decision as to which algorithm to use based on comparative analysis. Finally, OpenRec is itself dynamically reconfigurable.