In this paper, we describe a set of software tools called the PRIDE ONTOlogy Editor (PRONTOE) and a methodology that allows system operators and domain experts to build and maintain ontologies of their systems with no explicit understanding of the underlying ontology representation. We present two case studies: one using NASA flight controllers, and another using the DARPA Robotic Challenge.

A fundamental requirement for success with technology that supports space operations, such as automated procedures and interactive plan generation, is that the technology must operate on valid models or ontologies of the application domain. Making these models is difficult because the data involved are voluminous, dynamic and come from a variety of sources and formats, so manual entry and maintenance is prohibitive. Using an ontological framework such as OWL can greatly alleviate this effort, but domain experts reason in domain terms, not the formal logic of ontologies. This paper describes an editing system that allows NASA domain experts to construct and maintain ontological information, and yet produce a standard form that can be manipulated by procedure authoring and execution, automated planning and other AI applications.

In this paper, we describe a specific approach to iterative planning in the domain of off-road route planning, in which the objective is to find a cost-minimal path from one point to another. In iterative planning we are concerned with finding a way to solve a succession of planning problems, improving the system’s behavior over time. For example, this improvement might come about through improved heuristics, leading to more effective search of the space of possible plans, or through corrections or additions to the domain model used in planning. In this work, we take the latter approach, modifying the domain model based on differences between plans generated using the existing model and “good” plans.

Real-time performance is a critical aspect of avionics computing. The Basic Avionics Lightweight Source Archetype (BALSA) exemplar provides a collection of Units of Conformance (UoCs) backed by a Future Airborne Capability Environment™ (FACE) Unit of Portability (UoP) Supplied Model (USM) running in a Linux desktop environment. This gives an easy-to-run example for users of the FACE Technical Standard and effectively illustrates the conformance aspects of the FACE Technical Standard, but is not intended to run with hard real-time constraints. To address this limitation, we developed Basswood, a BALSA-based exemplar using components aligned to the FACE Technical Standard running in a real-time environment. Basswood runs on Real-Time Executive for Multiprocessor Systems (RTEMS), an open source Real-time Operating System (RTOS). Further, Basswood facilitates a practical demonstration of model-based systems engineering using the Architecture Analysis and Design Language (AADL). Basswood helps demonstrate how combined use of the FACE Technical Standard and AADL allows application of virtual integration analysis methods to FACE UoCs. This paper describes the lessons we learned adapting BALSA to a real-time environment and introduces readers to virtual integration analysis with the FACE Technical Standard and AADL.

Challenging problems associated with system software complexity growth are threatening industry’s ability to build next-generation safety-critical embedded systems, including helicopter avionics systems. Contributors to these problems include the growth of software, system integration, and interaction complexity exacerbated by ambiguous, missing, incomplete, and inconsistent requirements. Problems continue to hamper systems in the areas of resource utilization, timing, safety, and security. A new approach called the Architecture-Centric Virtual Integration Process (ACVIP), which is based on Society of Automotive Engineers (SAE) Standard AS5506A Architecture Analysis and Design Language (AADL), is being developed and investigated by the U.S. Army to address these challenges. ACVIP is a quantitative, architecture-centric, model-based approach enabling virtual integration analysis in the early phases and throughout the lifecycle to detect and remove defects that currently are not found until software and systems integration and acceptance testing. In an effort to investigate such an approach, the government, in conjunction with researchers from the Carnegie Mellon University (CMU) Software Engineering Institute (SEI) and Adventium Labs®, is conducting ACVIP requirements, safety, and timing analyses in parallel with the Joint Common Architecture (JCA) Demonstration (Demo).

In traditional design methodologies, the system designer typically develops the application in a sequential paradigm almost to completion before addressing issues of parallelism and mapping to a heterogeneous architecture. As the architectural complexity of these applications increase, however, this process becomes too costly since implementation must be started anew after the design. The quality of the design also often suffers as a result. This is especially true for embedded applications, where the complexity lies within the system software and hardware architecture. We present a new methodology and toolset aimed at improving the system development process for high-performance embedded applications. The toolset provides a unified design representation from early design specification to integration—allowing for parallelism and synchronization specification in domain specific styles, and automating many process steps such as partitioning/mapping, simulation, glue-code generation, and performance analysis.

Cyber-Physical Systems (CPS) are software and hardware systems that interact with the physical environment. Many CPSs have useful lifetimes measured in decades. This leads to unique concerns regarding security and longevity of software designed for CPSs which are exacerbated by the need for CPSs to adapt to ecosystem changes if theyare to remain functional over extended periods. In particular, the software in long-lifetime CPSs must adapt to unanticipated trends in environmental conditions, aging effects on mechanical systems, and component upgrades and modifications. This paper presents the Toolkit for Evolving Ecosystem Envelopes (TEEE) system created to help address these challenges in CPSs. TEEE is able to detect environmental changes which have caused errors within the CPS without directly sensing the environmental change. TEEE uses dynamic profiling to detect the errors within the CPS, determine the root cause of the error, alert the user, and suggest a possible adaption.

Constructing, maintaining, modifying, and adapting operational procedures for manned space operations is a complex task. The procedure author is required to keep track of state constraints such as the location of personnel, equipment, or tools, and of resources such as oxygen, fuel, or power. They must also keep in mind a set of constraints imposing additional restrictions on these procedures. For operations on the International Space Station (ISS), these constraints may be of several different types, including such things as warnings that must be present for a given type of operation, previous actions that must have been taken, tracking the location of personnel, tools, and equipment, or synchronizing operations by different astronauts.
As part of an ongoing research project funded by NASA, Adventium Labs and TRACLabs have designed and implemented an initial version of the Constraint Checking Editor for Procedure Tracking (ConCEPT) system, a constraint checking system for procedures represented in the Procedure Representation Language (PRL). ConCEPT has been integrated into TRACLabs’ Procedure Integrated Development Environment (PrIDE), so that procedures in PRL can be checked against constraints and modified during the process of procedure authoring. The design of ConCEPT, including the types of constraints considered and the integration into the PrIDE user interface, has been validated in discussions with NASA flight controllers.

ISO 14971, the primary medical device risk management standard focuses on single-manufacturer monolithic devices. However, the trend towards medical systems built from reusable platforms and interoperable components produced by different manufacturers introduces a number of additional risk management challenges. In this paper, we revisit the stages of the ISO 14971 risk management process, identify risk management challenges associated with interoperable medical systems that are not sufficiently addressed in ISO 14971, and we discuss possible process, analysis, and management concepts that may be useful in addressing these challenges.

FUSED is a tool integration framework that supports multiple engineers who are collaborating in the development of a diverse set of engineering models used for multiple purposes in multiple phases of development. FUSED is extensible to support a chosen set of modeling environments; a few examples from our work are requirements, solid geometry, computational fluid dynamics, dynamical systems, and vetronics/avionics. An extensible language approach is used, so that many FUSED capabilities are presented to domain experts as minor additions to familiar languages and tools. There is also a special FUSED language to specify compositions of models. Compositions may be used for multiple purposes, e.g., to specify multiple views of a component, verify inter- model consistency, specify part/whole assemblies, or apply design operations to models. One goal of FUSED is to reduce errors due to inconsistencies and emergent properties that occur across multiple models being developed by multiple domain-specific experts. For example, FUSED has an extensible typing and meta-typing system, and compositions may include powerful model verification environments. Another goal is improved support for concurrent, collaborative, mixed- initiative, evolutionary development processes. For example, FUSED was designed to support dependency tracking, change management and ripple effects analyses, version control and remote model server access, and mixed-initiative and multi- disciplinary collaborative optimization.