Philip S. Barry

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This paper examines the use of Bayesian Networks to tackle one of the tougher problems in requirements engineering, translating user requirements into system requirements. The approach taken is to model domain knowledge as Bayesian Network fragments that are glued together to form a complete view of the domain specific system requirements. User requirements(More)
r e q u i r e m e n t s c a l l e d a s y s t e m r e q u i r e m e n t w e b ( S R W ) . A S R W i s a d i r e c t e d g r a p h i n w h i c h t h e n o d e s r e p r e s e n t s y s t e m r e q u i r e m e n t s a n d t h e e d g e s r e p r e s e n t r e l a t i o n s h i p s b e t w e e n r e q u i r e m e n t s t h a t w e c a l l w e a k i m p l i c a(More)
Effective requirements management has been recognized as a key element in the creation of systems. This exercise involves a significant amount of uncertainty, as the requirements analyst is often unsure if the system requirements specified actually provide the functionality the user wants. Previous work demonstrated how system functionality within a given(More)
This paper briefly introduces the inherent challenges to Systems of Systems engineering. A solution created by the authors is then described, the Infrastructure for Complex-systems Engineering (ICE). The paper concludes with two case studies making use of various aspects of the ICE. The first is an application to large venue protection; the second is an(More)
Data Farming leverages high performance computing to run simple models many times. This process allows for the exploration of massive parameter spaces relatively quickly. This paper explores a methodology to use Data Farming as a decision support tool. Data Farming can be a highly effective in this role because it allows one to present to a decision-maker(More)
As the fielding of enterprise systems of systems becomes common it becomes increasingly important to understand the interactions between the systems as well as the important role that human behavior plays. This paper suggests that Agent-Directed Simulation is a valuable and crucial analysis tool for the Systems Engineer. The paper examines the concept of(More)
In the spring of 2005 a limited objective experiment was carried out to assess the feasibility of using agent based simulations to enhance co-evolutionary course of action development. In particular, relatively low fidelity simulations were employed to visualize the results of particular courses of action. Over four days multiple courses of action were(More)
This paper discusses the problem of modeling phenomena with a low base rate of occurrence using terrorism as an example. The paper suggests that Data Farming—developing data sets through utilization of massive computation—may be a useful way to deal with this challenge. An abstract model is described and analyzed as a simple case study. Preliminary results(More)
The Marine Corps' Project Albert seeks to model complex phenomenon by observing the behavior of relatively simple simulations over thousands of runs. A rich data base is developed by running the simulations thousands of times, varying the agent and scenario input parameters as well as the random seeds. Exploring this result space may provide significant(More)