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Troubleshooting why a constraint fails for a path is likely to be a very frustrating process unless we can do some kind of constraint violation localization to track down where the problem is. Otherwise, the fault could be literally anywhere: a single property of a single port within a single state, for example. However, there are significant theoretical challenges to doing this kind of localization. A key purpose of evolution styles is to facilitate trade-off-based reasoning. This can be accomplished through the definition of a utility evaluation function as a weighted composite of other functions that evaluate more primitive qualities such as cost, duration, availability, and so on. But if this utility function is hard-coded in an evolution style, how can we give style users the flexibility to explore the trade-off space by adjusting these weights? What features can we provide to facilitate easy 164 8. Better yet, is it possible to automate the trade-off analysis, and to present the user with a meaningful summary of the trade-offs among paths? Can we automatically characterize the most significant distinguishing factors among the paths? Automatically identifying these trade-offs and presenting them in a helpful way presents a number of challenges. For example, in an evolution involving the migration and redeployment of software components, it would likely be helpful to consider both a component-and-connector view and a deployment view of the system. How can relationships across views and across models be represented?
But relating different types of models—say, an Acme component-and-connector view and a UML class diagram representing a module view—is much harder. How can an Acme model incorporate references to a UML diagram, or vice versa? And how can the integrity of such references be enforced and preserved as the models change?
How can other system views besides conventional architectural views be used to inform evolution planning? By including other, nonarchitectural system views, we can gain significant analytical leverage. For example, given the importance of human factors in system evolution, it might be useful to have an organizational view alongside the architectural views. Such a view could contain information on development teams and their respective competencies and specialties. With such a view defined, we could define constraints restricting which teams can work on which parts of the system and which skills are required for which tasks, operators that effect 165 8 Conclusion organizational transformations such as restructuring or training a development team, and evaluation functions that make use of information in the organizational view to estimate concerns such as cost and effort in a more precise way. But although this idea is appealing in principle, it is not clear what guiding principles should govern the introduction of nonarchitectural views, or how such views might be defined or related to other views.
But what modifications must be made to our constraint specification language to accommodate such constraints? Currently, the constraint specification language relies on the architectural modeling language to provide a way of specifying architectural predicates. But what happens when there are multiple architectural modeling languages, each with its own way of specifying architectural predicates?
How can tools be developed that support multiple views?
But few architecture modeling tools provide good support for modeling and relating multiple views of a system. Thus, the introduction of support for multiple views significantly complicates implementation. An architect defines a single evolution graph in which each state contains a complete representation of the system.
In the evolution of a very large system, there may be many architects and engineers, each with responsibility for some small portion of the overall best site to buy a research paper architecture.
Large evolution efforts require different teams to focus on different 166 8.
Often, different architects will plan different aspects of the evolution. One might imagine some kind of distributed system in which different architects work on a shared evolution model, with some system of permissions to determine which architects may work on which portions of the system, but there are numerous questions about how this idea could be realized. How can we extend our approach to accommodate parallel execution of evolution operators? The assumption of sequential application of operators is ingrained in our model. The evolution graph is defined in terms of transitions comprising sequences of operators. Constraints are defined in a logic that presumes a linear evolution path. And operators themselves are defined in a language that assumes that an operator has perfect knowledge about, and exclusive control over, the state of the entire system for the duration of its application.
To accommodate definition of operators occurring in parallel, we would i need someone to write my research paper need to throw out all these assumptions, revisiting each element of our modeling approach. An evolution path might be conceived as comprising multiple parallel threads of effort. The operator specification language would need to be reinvented to accommodate the fact that multiple operators may be occurring in parallel. For example, we now must consider the possibility of conflicts among operators occurring in parallel (e.
And the path constraint specification language would need to be redefined as well. If an evolution path is a best site to buy a research paper set of parallel threads rather than a linear sequence, then linear temporal logic may no longer be a good basis for our path constraint language. Sociotechnical ecosystems have become an increasingly hot topic in software research. How can the architecture of a sociotechnical ecosystem be best site to buy a research paper changed in a principled manner? Evolving a system when there is no single entity that has control over that system is a challenging prospect. How can such evolution be planned in the face of radical uncertainty about the actions of other ecosystem participants? While this work is a useful first step, there are many significant research questions that remain before such automation can be made practical. How best site to buy a research paper can we best generate multiple candidate paths and present them to the user? However, it might be desirable to keep the architect in the loop. However, it is not clear how we might best generate multiple paths. One option might be to run the planner multiple times, each time optimizing a different metric. How can we model transitions consisting of multiple evolution operators? This streamlines the evolution graph, making it more comprehensible to architects and simplifying analysis.
In our automated-planning work, however, we treated evolution operators as synonymous with the evolution graph transitions. It would be better for a planner to best site to buy a research paper aggregate operators into larger transitions by identifying particularly significant points within the evolution to serve as the nodes of the evolution path. However, it is not clear on what basis it should select these significant points.
That is, although the generation of the evolution paths was automated, the definition of the scenario in PDDL was not.