Debugging real-time software in a host-target environment

A common paradigm for the development of process-control or embedded computer software is to do most of the implementation and testing on a large host computer, then retarget the code for final checkout and production execution on the target machine. The host machine is usually large and provides a variety of program development tools, while the target may be a small, bare machine. A difficulty with the paradigm arises when the software developed has real-time constraints and is composed of multiple communicating processes. If a test execution on the target fails, it may be exceptionally tedious to determine the cause of the failure. Host machine debuggers cannot normally be applied, because the same program processing the same data will frequently exhibit different behavior on the host. Differences in processor speed, scheduling algorithm, and the like, account for the disparity. This paper proposes a partial solution to this problem, in which the errant execution reconstructed and made amenable to source language level debugging on the host. The solution involves the integrated application of a static concurrency analyzer, an interactive interpreter, and a graphical program visualization aid. Though generally applicable, the solution is described here in the context of multi-tasked real-time Ada* programs

An environment for object-oriented real-time system design

A concise object-oriented method for the development of real-time systems has been composed. Hardware components are modelled by (software) base objects; base objects are controlled by a hierarchy of coordinator objects, expressed in an organizational diagram. The behaviour of objects is specified by state transition diagrams. This approach considerably promotes requirements analysis and communication with the customer. A CASE tool has been constructed with diagram editors for graphical specifications of real-time systems. The tool can generate executable code for PLCs from these graphical specifications; reuse of previous results is supported by the repository function of the tool. Experiences attained in practice with method and tool show that time spent in system testing and installation is reduced considerabl

An intelligent processing environment for real-time simulation

The development of a highly efficient and thus truly intelligent processing environment for real-time general purpose simulation of continuous systems is described. Such an environment can be created by mapping the simulation process directly onto the University of Alamba's OPERA architecture. To facilitate this effort, the field of continuous simulation is explored, highlighting areas in which efficiency can be improved. Areas in which parallel processing can be applied are also identified, and several general OPERA type hardware configurations that support improved simulation are investigated. Three direct execution parallel processing environments are introduced, each of which greatly improves efficiency by exploiting distinct areas of the simulation process. These suggested environments are candidate architectures around which a highly intelligent real-time simulation configuration can be developed

Decoherence, wave function collapses and non-ordinary statistical mechanics

We consider a toy model of pointer interacting with a 1/2-spin system, whose $\sigma_{x}$ variable is \emph{measured} by the environment, according to the prescription of decoherence theory. If the environment measuring the variable $\sigma_{x}$ yields ordinary statistical mechanics, the pointer sensitive to the 1/2-spin system undergoes the same, exponential, relaxation regardless of whether real collapses or an entanglement with the environment, mimicking the effect of real collapses, occur. In the case of non-ordinary statistical mechanics the occurrence of real collapses make the pointer still relax exponentially in time, while the equivalent picture in terms of reduced density matrix generates an inverse power law relaxation

Execution environment for intelligent real-time control systems

Modern telerobot control technology requires the integration of symbolic and non-symbolic programming techniques, different models of parallel computations, and various programming paradigms. The Multigraph Architecture, which has been developed for the implementation of intelligent real-time control systems is described. The layered architecture includes specific computational models, integrated execution environment and various high-level tools. A special feature of the architecture is the tight coupling between the symbolic and non-symbolic computations. It supports not only a data interface, but also the integration of the control structures in a parallel computing environment