Modern computing technologies-hardware, software, and algorithmic-have enabled the deployment of more exacting diagnostic reasoning (DR) systems than has heretofore been possible. Compromises in algorithm and modeling paradigm complexity, due to computational throughput and state-space explosion constraints, have historically dominated practical applications of such systems. This paper describes approaches that have been shown to be applicable in a wide set of domains. The algorithms used are highly scaleable and support a symbolic modeling formalism for analyzing the properties of the complex, dynamic systems. Moreover, analysis of simultaneous failures occurs as a natural byproduct of this formalism.

Many large software systems are tightly integrated with their physical environments and must be adapted when their environment changes. Typically, software development methodologies do not place a great emphasis on modeling the system's environment, and hence environmental changes may lead to significant and complicated changes in the software. We argue that (1) the modeling of the environment should be an integral part of the process, and (2) to support software evolution, wherever possible, the software should be automatically generated. We present a model-integrated development approach that is capable of supporting cost effective system evolution in accordance with changes in the system's environment. The approach is supported by a "meta-architecture" that provides a framework for building model-based systems. This framework has been successfully used in various projects. One of these projects, a site-production flow visualization system for a large manufacturing operation, is analyzed in detail.

The design, implementation and deployment of computer applications tightly integrated with complex, changing environments is a difficult task. This paper presents the Multigraph Architecture (MGA) developed for building complex embedded systems. The MGA is a meta-level architecture which includes tools and methods to create domain specific model integrated program synthesis environments. These environments support the integrated modeling of systems independently from their implementation, include tools for model analysis and application specific model interpreters for the synthesis of executable programs.

This paper presents a rigorous approach to automatic generation of schematic diagrams for digital systems described as networks of modules. This is very useful in comprehensive CAD environment. The approach is based on identification of some guidelines which are traditionally followed in manual drawing of schematic diagrams. Theses guidelines are transformed into quantitative objectives. In view of the complex interrelationship between these objectives, the schematic design process is broken into a long sequence of steps. An attempt is made to give rigorous formulation for each step, along with efficient solutions, making suitable approximations where necessary. An illustrative diagram generated using these algorithms is included showing that the results compare well with hand drawn diagrams.