Development of an Intelligent Monitoring and Control System for a Heterogeneous Numerical Propulsion System Simulation

The NASA Numerical Propulsion System Simulation (NPSS) project is exploring the use of computer simulation to facilitate the design of new jet engines. Several key issues raised in this research are being examined in an NPSS-related research project: zooming, monitoring and control, and support for heterogeneity. The design of a simulation executive that addresses each of these issues is described. In this work, the strategy of zooming, which allows codes that model at different levels of fidelity to be integrated within a single simulation, is applied to the fan component of a turbofan propulsion system. A prototype monitoring and control system has been designed for this simulation to support experimentation with expert system techniques for active control of the simulation. An interconnection system provides a transparent means of connecting the heterogeneous systems that comprise the prototype

Behavioural model debugging in Linda

This thesis investigates event-based behavioural model debugging in Linda. A study is presented of the Linda parallel programming paradigm, its amenability to debugging, and a model for debugging Linda programs using Milner's CCS. In support of the construction of expected behaviour models, a Linda program specification language is proposed. A behaviour recognition engine that is based on such specifications is also discussed. It is shown that Linda's distinctive characteristics make it amenable to debugging without the usual problems associated with paraUel debuggers. Furthermore, it is shown that a behavioural model debugger, based on the proposed specification language, effectively exploits the debugging opportunity. The ideas developed in the thesis are demonstrated in an experimental Modula-2 Linda system

Designing Diagnosable Distributed Programs.

The difficulty in debugging distributed programs motivates the development of formal methods for designing distributed programs that are easier to debug and maintain. We address state identification problem for distributed systems using the finite state I/O automaton model. A state S is identified based on the unique event sequences starting at S, called distinguishing sequences. An automaton is diagnosable if every state has a distinguishing sequence. A distributed program may not be diagnosable even if its components are diagnosable. Non-dignosable automata can, in some cases, be converted to a diagnosable form by relabelling some of its transitions in a way that preserves the semantics of the program. Not all automata can be converted to a diagnosable form in this way. This is due to inherent ill-posedness of specification. Two algorithms to convert a non-diagnosable automaton to a diagnosable form are presented. Debugging is the controlled execution of one program by another. The latter is called the supervisor of the former. The supervision operation is defined so that the debugging of a distributed program by distributed debuggers is reduced to the same as the debugging of a single program by a single debugger. An algorithm to construct a debugger for a diagnosable program is developed. Every diagnosable program has a unique debugger associated with it. This leads to the introduction of the notion of debugging complexity of programs