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Pecheur, Charles

Publications and source records attributed to Pecheur, Charles.

State Event Models for the Formal Analysis of Human-Machine Interactions

The work described in this paper was motivated by our experience with applying a framework for formal analysis of human-machine interactions (HMI) to a realistic model of an autopilot. The framework is built around a formally defined conformance relation called "fullcontrol" between an actual system and the mental model according to which the system is operated. Systems are well-designed if they can be described by relatively simple, full-control, mental models for their human operators. For this reason, our framework supports automated generation of minimal full-control mental models for HMI systems, where both the system and the mental models are described as labelled transition systems (LTS). The autopilot that we analysed has been developed in the NASA Ames HMI prototyping tool ADEPT. In this paper, we describe how we extended the models that our HMI analysis framework handles to allow adequate representation of ADEPT models. We then provide a property-preserving reduction from these extended models to LTSs, to enable application of our LTS-based formal analysis algorithms. Finally, we briefly discuss the analyses we were able to perform on the autopilot model with our extended framework.

State-event Models

Verifying Diagnostic Software

Livingstone PathFinder (LPF) is a simulation-based computer program for verifying autonomous diagnostic software. LPF is designed especially to be applied to NASA s Livingstone computer program, which implements a qualitative-model-based algorithm that diagnoses faults in a complex automated system (e.g., an exploratory robot, spacecraft, or aircraft). LPF forms a software test bed containing a Livingstone diagnosis engine, embedded in a simulated operating environment consisting of a simulator of the system to be diagnosed by Livingstone and a driver program that issues commands and faults according to a nondeterministic scenario provided by the user. LPF runs the test bed through all executions allowed by the scenario, checking for various selectable error conditions after each step. All components of the test bed are instrumented, so that execution can be single-stepped both backward and forward. The architecture of LPF is modular and includes generic interfaces to facilitate substitution of alternative versions of its different parts. Altogether, LPF provides a flexible, extensible framework for simulation-based analysis of diagnostic software; these characteristics also render it amenable to application to diagnostic programs other than Livingstone.

Lindsey, Tony

Simulation-Based Verification of Autonomous Controllers via Livingstone PathFinder

AI software is often used as a means for providing greater autonomy to automated systems, capable of coping with harsh and unpredictable environments. Due in part to the enormous space of possible situations that they aim to addrs, autonomous systems pose a serious challenge to traditional test-based verification approaches. Efficient verification approaches need to be perfected before these systems can reliably control critical applications. This publication describes Livingstone PathFinder (LPF), a verification tool for autonomous control software. LPF applies state space exploration algorithms to an instrumented testbed, consisting of the controller embedded in a simulated operating environment. Although LPF has focused on NASA s Livingstone model-based diagnosis system applications, the architecture is modular and adaptable to other systems. This article presents different facets of LPF and experimental results from applying the software to a Livingstone model of the main propulsion feed subsystem for a prototype space vehicle.

Lindsey, A. E.

Simulation-Based Verification of Livingstone Applications

AI software is viewed as a means to give greater autonomy to automated systems, capable of coping with harsh and unpredictable environments in deep space missions. Autonomous systems pose a serious challenge to traditional test-based verification approaches, because of the enormous space of possible situations that they aim to address. Before these systems are put in control of critical applications, appropriate new verification approaches need to be developed. This article describes Livingstone PathFinder (LPF), a verification tool for autonomous diagnosis applications based on NASA's Livingstone model-based diagnosis system. LPF applies state space exploration algorithms to an instrumented testbed, consisting of the Livingstone diagnosis system embedded in a simulated operating environment. The article describes different facets of LPF and reports some experimental results from applying LPF to a Livingstone model of the main propulsion feed subsystem of the X-34 space vehicle. This paper describes Livingstone PathFinder (LPF), a verification tool for autonomous diagnosis applications based on NASA's Livingstone model-based diagnosis system. LPF applies state space exploration algorithms to an instrumented testbed, consisting of the Livingstone diagnosis system embedded in a simulated operating environment. Section 2 provides an overview of Livingstone; Section 3 describes the LPF architecture; Section 4 discusses its applicability; Section 5 reviews some experimental results; Section 6 compares LPF to related verification approaches; Section 7 draws conclusions and discusses some perspectives.

Lindsey, Anthony E.

Practical Formal Verification of Diagnosability of Large Models via Symbolic Model Checking

This document reports on the activities carried out during a four-week visit of Roberto Cavada at the NASA Ames Research Center. The main goal was to test the practical applicability of the framework proposed, where a diagnosability problem is reduced to a Symbolic Model Checking problem. Section 2 contains a brief explanation of major techniques currently used in Symbolic Model Checking, and how these techniques can be tuned in order to obtain good performances when using Model Checking tools. Diagnosability is performed on large and structured models of real plants. Section 3 describes how these plants are modeled, and how models can be simplified to improve the performance of Symbolic Model Checkers. Section 4 reports scalability results. Three test cases are briefly presented, and several parameters and techniques have been applied on those test cases in order to produce comparison tables. Furthermore, comparison between several Model Checkers is reported. Section 5 summarizes the application of diagnosability verification to a real application. Several properties have been tested, and results have been highlighted. Finally, section 6 draws some conclusions, and outlines future lines of research.

Cavada, Roberto

Formal Verification for a Next-Generation Space Shuttle

This paper discusses the verification and validation (V&2) of advanced software used for integrated vehicle health monitoring (IVHM), in the context of NASA's next-generation space shuttle. We survey the current VBCV practice and standards used in selected NASA projects, review applicable formal verification techniques, and discuss their integration info existing development practice and standards. We also describe two verification tools, JMPL2SMV and Livingstone PathFinder, that can be used to thoroughly verify diagnosis applications that use model-based reasoning, such as the Livingstone system.

Nelson, Stacy D.

Survey of NASA V and V Processes/Methods

The purpose of this report is to describe current NASA Verification and Validation (V&V) techniques and to explain how these techniques are applicable to 2nd Generation RLV Integrated Vehicle Health Management (IVHM) software. It also contains recommendations for special V&V requirements for IVHM. This report is divided into the following three sections: 1) Survey - Current NASA V&V Processes/Methods; 2) Applicability of NASA V&V to 2nd Generation RLV IVHM; and 3) Special 2nd Generation RLV IVHM V&V Requirements.

Pecheur, Charles

New V and V Tools for Diagnostic Modeling Environment (DME)

The purpose of this report is to provide correctness and reliability criteria for verification and validation (V&V) of Second Generation Reusable Launch Vehicle (RLV) Diagnostic Modeling Environment, describe current NASA Ames Research Center tools for V&V of Model Based Reasoning systems, and discuss the applicability of Advanced V&V to DME. This report is divided into the following three sections: (1) correctness and reliability criteria; (2) tools for V&V of Model Based Reasoning; and (3) advanced V&V applicable to DME. The Executive Summary includes an overview of the main points from each section. Supporting details, diagrams, figures, and other information are included in subsequent sections. A glossary, acronym list, appendices, and references are included at the end of this report.

Pecheur, Charles

RIACS Workshop on the Verification and Validation of Autonomous and Adaptive Systems

The long-term future of space exploration at NASA is dependent on the full exploitation of autonomous and adaptive systems: careful monitoring of missions from earth, as is the norm now, will be infeasible due to the sheer number of proposed missions and the communication lag for deep-space missions. Mission managers are however worried about the reliability of these more intelligent systems. The main focus of the workshop was to address these worries and hence we invited NASA engineers working on autonomous and adaptive systems and researchers interested in the verification and validation (V&V) of software systems. The dual purpose of the meeting was to: (1) make NASA engineers aware of the V&V techniques they could be using; and (2) make the V&V community aware of the complexity of the systems NASA is developing.

Pecheur, Charles

Verification and Validation of Model-Based Autonomous Systems

This paper presents a three year project (FY99 to FY01) on the verification and validation of model based autonomous systems. The topics include: 1) Project Profile; 2) Model-Based Autonomy; 3) The Livingstone MIR; 4) MPL2SMV; 5) Livingstone to SMV Translation; 6) Symbolic Model Checking; 7) From Livingstone Models to SMV Models; 8) Application In-Situ Propellant Production; 9) Closed-Loop Verification Principle; 10) Livingstone PathFinder (LPF); 11) Publications and Presentations; and 12) Future Directions. This paper is presented in viewgraph form.

Pecheur, Charles

Formal Analysis of the Remote Agent Before and After Flight

This paper describes two separate efforts that used the SPIN model checker to verify deep space autonomy flight software. The first effort occurred at the beginning of a spiral development process and found five concurrency errors early in the design cycle that the developers acknowledge would not have been found through testing. This effort required a substantial manual modeling effort involving both abstraction and translation from the prototype LISP code to the PROMELA language used by SPIN. This experience and others led to research to address the gap between formal method tools and the development cycle used by software developers. The Java PathFinder tool which directly translates from Java to PROMELA was developed as part of this research, as well as automatic abstraction tools. In 1999 the flight software flew on a space mission, and a deadlock occurred in a sibling subsystem to the one which was the focus of the first verification effort. A second quick-response "cleanroom" verification effort found the concurrency error in a short amount of time. The error was isomorphic to one of the concurrency errors found during the first verification effort. The paper demonstrates that formal methods tools can find concurrency errors that indeed lead to loss of spacecraft functions, even for the complex software required for autonomy. Second, it describes progress in automatic translation and abstraction that eventually will enable formal methods tools to be inserted directly into the aerospace software development cycle.

Havelund, Klaus

Verification and Validation of Autonomy Software at NASA

Autonomous software holds the promise of new operation possibilities, easier design and development and lower operating costs. However, as those system close control loops and arbitrate resources on board with specialized reasoning, the range of possible situations becomes very large and uncontrollable from the outside, making conventional scenario-based testing very inefficient. Analytic verification and validation (V&V) techniques, and model checking in particular, can provide significant help for designing autonomous systems in a more efficient and reliable manner, by providing a better coverage and allowing early error detection. This article discusses the general issue of V&V of autonomy software, with an emphasis towards model-based autonomy, model-checking techniques and concrete experiments at NASA.

Pecheur, Charles

From Livingstone to SMV: Formal Verification for Autonomous Spacecrafts

To fulfill the needs of its deep space exploration program, NASA is actively supporting research and development in autonomy software. However, the reliable and cost-effective development and validation of autonomy systems poses a tough challenge. Traditional scenario-based testing methods fall short because of the combinatorial explosion of possible situations to be analyzed, and formal verification techniques typically require a tedious, manual modelling by formal method experts. This paper presents the application of formal verification techniques in the development of autonomous controllers based on Livingstone, a model-based health-monitoring system that can detect and diagnose anomalies and suggest possible recovery actions. We present a translator that converts the models used by Livingstone into specifications that can be verified with the SMV model checker. The translation frees the Livingstone developer from the tedious conversion of his design to SMV, and isolates him from the technical details of the SMV program. We describe different aspects of the translation and briefly discuss its application to several NASA domains.

Pecheur, Charles

Verification and Validation of Autonomy Software at NASA

Autonomous software holds the promise of new operation possibilities, easier design and development, and lower operating costs. However, as those system close control loops and arbitrate resources on-board with specialized reasoning, the range of possible situations becomes very large and uncontrollable from the outside, making conventional scenario-based testing very inefficient. Analytic verification and validation (V&V) techniques, and model checking in particular, can provide significant help for designing autonomous systems in a more efficient and reliable manner, by providing a better coverage and allowing early error detection. This article discusses the general issue of V&V of autonomy software, with an emphasis towards model-based autonomy, model-checking techniques, and concrete experiments at NASA.

Pecheur, Charles

Using Model Checking to Validate AI Planner Domain Models

This report describes an investigation into using model checking to assist validation of domain models for the HSTS planner. The planner models are specified using a qualitative temporal interval logic with quantitative duration constraints. We conducted several experiments to translate the domain modeling language into the SMV, Spin and Murphi model checkers. This allowed a direct comparison of how the different systems would support specific types of validation tasks. The preliminary results indicate that model checking is useful for finding faults in models that may not be easily identified by generating test plans.

Penix, John