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At least 487 records · Page 27

Design for Verification: Using Design Patterns to Build Reliable Systems

Components so far have been mainly used in commercial software development to reduce time to market. While some effort has been spent on formal aspects of components, most of this was done in the context of programming language or operating system framework integration. As a consequence, increased reliability of composed systems is mainly regarded as a side effect of a more rigid testing of pre-fabricated components. In contrast to this, Design for Verification (D4V) puts the focus on component specific property guarantees, which are used to design systems with high reliability requirements. D4V components are domain specific design pattern instances with well-defined property guarantees and usage rules, which are suitable for automatic verification. The guaranteed properties are explicitly used to select components according to key system requirements. The D4V hypothesis is that the same general architecture and design principles leading to good modularity, extensibility and complexity/functionality ratio can be adapted to overcome some of the limitations of conventional reliability assurance measures, such as too large a state space or too many execution paths.

Mehlitz, Peter C.↗

General Environmental Verification Specification

The NASA Goddard Space Flight Center s General Environmental Verification Specification (GEVS) for STS and ELV Payloads, Subsystems, and Components is currently being revised based on lessons learned from GSFC engineering and flight assurance. The GEVS has been used by Goddard flight projects for the past 17 years as a baseline from which to tailor their environmental test programs. A summary of the requirements and updates are presented along with the rationale behind the changes. The major test areas covered by the GEVS include mechanical, thermal, and EMC, as well as more general requirements for planning, tracking of the verification programs.

Milne, J. Scott, Jr.↗

Experimental Evaluation of Verification and Validation Tools on Martian Rover Software

To achieve its science objectives in deep space exploration, NASA has a need for science platform vehicles to autonomously make control decisions in a time frame that excludes intervention from Earth-based controllers. Round-trip light-time is one significant factor motivating autonomy capability, another factor is the need to reduce ground support operations cost. An unsolved problem potentially impeding the adoption of autonomy capability is the verification and validation of such software systems, which exhibit far more behaviors (and hence distinct execution paths in the software) than is typical in current deepspace platforms. Hence the need for a study to benchmark advanced Verification and Validation (V&V) tools on representative autonomy software. The objective of the study was to access the maturity of different technologies, to provide data indicative of potential synergies between them, and to identify gaps in the technologies with respect to the challenge of autonomy V&V. The study consisted of two parts: first, a set of relatively independent case studies of different tools on the same autonomy code, second a carefully controlled experiment with human participants on a subset of these technologies. This paper describes the second part of the study. Overall, nearly four hundred hours of data on human use of three different advanced V&V tools were accumulated, with a control group that used conventional testing methods. The experiment simulated four independent V&V teams debugging three successive versions of an executive controller for a Martian Rover. Defects were carefully seeded into the three versions based on a profile of defects from CVS logs that occurred in the actual development of the executive controller. The rest of the document is structured a s follows. In section 2 and 3, we respectively describe the tools used in the study and the rover software that was analyzed. In section 4 the methodology for the experiment is described; this includes the code preparation, seeding of defects, participant training and experimental setup. Next we give a qualitative overview of how the experiment went from the point of view of each technology; model checking (section 5), static analysis (section 6), runtime analysis (section 7) and testing (section 8). The find section gives some preliminary quantitative results on how the tools compared.

Brat, Guillaume↗

Real-Time Embedded Software Verification and Validation 2001

As the space applications become more complex and timing constraints on control actions are more stringent, the task of integrating and testing NASA's real-time systems (such as X-38 Crew Return Vehicle, and certain International Space Station autonomous systems) has become a great challenge. A testing environment where can preserve consistent temporal behaviors as in the target execution must be established for system-level verification and software quality assurance. Our goal is to develop an analysis suite for validation and verification of real-time systems that are used to perform human- in-the-loop control operations during safety-critical missions. The suite will be able to carry out quantitative approaches of coverage diagnostic and temporal behavior evaluation in order to measure test coverage, to optimize test utilization, and to verify timing correctness.

Lee, Yann-Hang↗

Verification and Validation Methodology of Real-Time Adaptive Neural Networks for Aerospace Applications

Recent research has shown that adaptive neural based control systems are very effective in restoring stability and control of an aircraft in the presence of damage or failures. The application of an adaptive neural network with a flight critical control system requires a thorough and proven process to ensure safe and proper flight operation. Unique testing tools have been developed as part of a process to perform verification and validation (V&V) of real time adaptive neural networks used in recent adaptive flight control system, to evaluate the performance of the on line trained neural networks. The tools will help in certification from FAA and will help in the successful deployment of neural network based adaptive controllers in safety-critical applications. The process to perform verification and validation is evaluated against a typical neural adaptive controller and the results are discussed.

Gupta, Pramod↗

Formal verification of human-automation interaction

This paper discusses a formal and rigorous approach to the analysis of operator interaction with machines. It addresses the acute problem of detecting design errors in human-machine interaction and focuses on verifying the correctness of the interaction in complex and automated control systems. The paper describes a systematic methodology for evaluating whether the interface provides the necessary information about the machine to enable the operator to perform a specified task successfully and unambiguously. It also addresses the adequacy of information provided to the user via training material (e.g., user manual) about the machine's behavior. The essentials of the methodology, which can be automated and applied to the verification of large systems, are illustrated by several examples and through a case study of pilot interaction with an autopilot aboard a modern commercial aircraft. The expected application of this methodology is an augmentation and enhancement, by formal verification, of human-automation interfaces.

Aviation↗

Abstraction and Assume-Guarantee Reasoning for Automated Software Verification

Compositional verification and abstraction are the key techniques to address the state explosion problem associated with model checking of concurrent software. A promising compositional approach is to prove properties of a system by checking properties of its components in an assume-guarantee style. This article proposes a framework for performing abstraction and assume-guarantee reasoning of concurrent C code in an incremental and fully automated fashion. The framework uses predicate abstraction to extract and refine finite state models of software and it uses an automata learning algorithm to incrementally construct assumptions for the compositional verification of the abstract models. The framework can be instantiated with different assume-guarantee rules. We have implemented our approach in the COMFORT reasoning framework and we show how COMFORT out-performs several previous software model checking approaches when checking safety properties of non-trivial concurrent programs.

Chaki, S.↗

Investigation of Navier-Stokes Code Verification and Design Optimization

With rapid progress made in employing computational techniques for various complex Navier-Stokes fluid flow problems, design optimization problems traditionally based on empirical formulations and experiments are now being addressed with the aid of computational fluid dynamics (CFD). To be able to carry out an effective CFD-based optimization study, it is essential that the uncertainty and appropriate confidence limits of the CFD solutions be quantified over the chosen design space. The present dissertation investigates the issues related to code verification, surrogate model-based optimization and sensitivity evaluation. For Navier-Stokes (NS) CFD code verification a least square extrapolation (LSE) method is assessed. This method projects numerically computed NS solutions from multiple, coarser base grids onto a freer grid and improves solution accuracy by minimizing the residual of the discretized NS equations over the projected grid. In this dissertation, the finite volume (FV) formulation is focused on. The interplay between the xi concepts and the outcome of LSE, and the effects of solution gradients and singularities, nonlinear physics, and coupling of flow variables on the effectiveness of LSE are investigated. A CFD-based design optimization of a single element liquid rocket injector is conducted with surrogate models developed using response surface methodology (RSM) based on CFD solutions. The computational model consists of the NS equations, finite rate chemistry, and the k-6 turbulence closure. With the aid of these surrogate models, sensitivity and trade-off analyses are carried out for the injector design whose geometry (hydrogen flow angle, hydrogen and oxygen flow areas and oxygen post tip thickness) is optimized to attain desirable goals in performance (combustion length) and life/survivability (the maximum temperatures on the oxidizer post tip and injector face and a combustion chamber wall temperature). A preliminary multi-objective optimization study is carried out using a geometric mean approach. Following this, sensitivity analyses with the aid of variance-based non-parametric approach and partial correlation coefficients are conducted using data available from surrogate models of the objectives and the multi-objective optima to identify the contribution of the design variables to the objective variability and to analyze the variability of the design variables and the objectives. In summary the present dissertation offers insight into an improved coarse to fine grid extrapolation technique for Navier-Stokes computations and also suggests tools for a designer to conduct design optimization study and related sensitivity analyses for a given design problem.

Vaidyanathan, Rajkumar↗

Development of Advanced Verification and Validation Procedures and Tools for the Certification of Learning Systems in Aerospace Applications

Adaptive control technologies that incorporate learning algorithms have been proposed to enable automatic flight control and vehicle recovery, autonomous flight, and to maintain vehicle performance in the face of unknown, changing, or poorly defined operating environments. In order for adaptive control systems to be used in safety-critical aerospace applications, they must be proven to be highly safe and reliable. Rigorous methods for adaptive software verification and validation must be developed to ensure that control system software failures will not occur. Of central importance in this regard is the need to establish reliable methods that guarantee convergent learning, rapid convergence (learning) rate, and algorithm stability. This paper presents the major problems of adaptive control systems that use learning to improve performance. The paper then presents the major procedures and tools presently developed or currently being developed to enable the verification, validation, and ultimate certification of these adaptive control systems. These technologies include the application of automated program analysis methods, techniques to improve the learning process, analytical methods to verify stability, methods to automatically synthesize code, simulation and test methods, and tools to provide on-line software assurance.

Jacklin, Stephen↗

Multi-Mission System Architecture Platform: Design and Verification of the Remote Engineering Unit

The Multi-Mission System Architecture Platform (MSAP) represents an effort to bolster efficiency in the spacecraft design process. By incorporating essential spacecraft functionality into a modular, expandable system, the MSAP provides a foundation on which future spacecraft missions can be developed. Once completed, the MSAP will provide support for missions with varying objectives, while maintaining a level of standardization that will minimize redesign of general system components. One subsystem of the MSAP, the Remote Engineering Unit (REU), functions by gathering engineering telemetry from strategic points on the spacecraft and providing these measurements to the spacecraft's Command and Data Handling (C&DH) subsystem. Before the MSAP Project reaches completion, all hardware, including the REU, must be verified. However, the speed and complexity of the REU circuitry rules out the possibility of physical prototyping. Instead, the MSAP hardware is designed and verified using the Verilog Hardware Definition Language (HDL). An increasingly popular means of digital design, HDL programming provides a level of abstraction, which allows the designer to focus on functionality while logic synthesis tools take care of gate-level design and optimization. As verification of the REU proceeds, errors are quickly remedied, preventing costly changes during hardware validation. After undergoing the careful, iterative processes of verification and validation, the REU and MSAP will prove their readiness for use in a multitude of spacecraft missions.

Sartori, John↗

Inspection and Verification of Domain Models with PlanWorks and Aver

When developing a domain model, it seems natural to bring the traditional informal tools of inspection and verification, debuggers and automated test suites, to bear upon the problems that will inevitably arise. Debuggers that allow inspection of registers and memory and stepwise execution have been a staple of software development of all sorts from the very beginning. Automated testing has repeatedly proven its considerable worth, to the extent that an entire design philosophy (Test Driven Development) has been developed around the writing of tests. Unfortunately, while not entirely without their uses, the limitations of these tools and the nature of the complexity of models and the underlying planning systems make the diagnosis of certain classes of problems and the verification of their solutions difficult or impossible. Debuggers provide a good local view of executing code, allowing a fine-grained look at algorithms and data. This view is, however, usually only at the level of the current scope in the implementation language, and the data-inspection capabilities of most debuggers usually consist of on-line print statements. More modem graphical debuggers offer a sort of tree view of data structures, but even this is too low-level and is often inappropriate for the kinds of structures created by planning systems. For instance, god or constraint networks are at best awkward when visualized as trees. Any any non-structural link between data structures, as through a lookup table, isn't captured at all. Further, while debuggers have powerful breakpointing facilities that are suitable for finding specific algorithmic errors, they have little use in the diagnosis of modeling errors.

Bedrax-Weiss, Tania↗

An Overview of NASA's IM&S Verification and Validation Process Plan and Specification for Space Exploration

NASA's Exploration Systems Mission Directorate (ESMD) is implementing a management approach for modeling and simulation (M&S) that will provide decision-makers information on the model's fidelity, credibility, and quality. This information will allow the decision-maker to understand the risks involved in using a model's results in the decision-making process. This presentation will discuss NASA's approach for verification and validation (V&V) of its models or simulations supporting space exploration. This presentation will describe NASA's V&V process and the associated M&S verification and validation (V&V) activities required to support the decision-making process. The M&S V&V Plan and V&V Report templates for ESMD will also be illustrated.

Gravitz, Robert M.↗

Verification and Validation in NASA-CUIP LOX/methane Injector Research Efforts

The NASA-CUIP program is supporting experimental and modeling/computational research efforts investigating wall heat flux characteristics of LOX/methane single-element injectors. A Verification and Validation (V&V) task has begun with the objective of quantifying the degree of accuracy of the models for wall heat flux distributions at specific sets of conditions. The V&V approach used is that being drafted as a standard by the ASME Performance Test Codes Committee, PTC 61: Verification and Validation in Computational Fluid Dynamics and Heat Transfer. The approach is based on well-established concepts from experimental uncertainty analysis. Initially the V&V and uncertainty estimation efforts will use data obtained previously in the same facility using oxygen/hydrogen in single-element injector testing. In this paper the V&V process, experimental facility, and computer code are described, and approaches to estimating the associated uncertainties are discussed.

Coleman, Hugh W.↗

Initial Verification of GEOS-4 Aerosols Using CALIPSO and MODIS: Scene Classification

A-train sensors such as MODIS and MISR provide column aerosol properties, and in the process a means of estimating aerosol type (e.g. smoke vs. dust). Correct classification of aerosol type is important because retrievals are often dependent upon selection of the right aerosol model. In addition, aerosol scene classification helps place the retrieved products in context for comparisons and analysis with aerosol transport models. The recent addition of CALIPSO to the A-train now provides a means of classifying aerosol distribution with altitude. CALIPSO level 1 products include profiles of attenuated backscatter at 532 and 1064 nm, and depolarization at 532 nm. Backscatter intensity, wavelength ratio, and depolarization provide information on the vertical profile of aerosol concentration, size, and shape. Thus similar estimates of aerosol type using MODIS or MISR are possible with CALIPSO, and the combination of data from all sensors provides a means of 3D aerosol scene classification. The NASA Goddard Earth Observing System general circulation model and data assimilation system (GEOS-4) provides global 3D aerosol mass for sulfate, sea salt, dust, and black and organic carbon. A GEOS-4 aerosol scene classification algorithm has been developed to provide estimates of aerosol mixtures along the flight track for NASA's Geoscience Laser Altimeter System (GLAS) satellite lidar. GLAS launched in 2003 and did not have the benefit of depolarization measurements or other sensors from the A-train. Aerosol typing from GLAS data alone was not possible, and the GEOS-4 aerosol classifier has been used to identify aerosol type and improve the retrieval of GLAS products. Here we compare 3D aerosol scene classification using CALIPSO and MODIS with the GEOS-4 aerosol classifier. Dust, smoke, and pollution examples will be discussed in the context of providing an initial verification of the 3D GEOS-4 aerosol products. Prior model verification has only been attempted with surface mass comparisons and column optical depth from AERONET and MODIS.

Welton, Ellsworth J.↗

NEXT Thruster Component Verification Testing

Component testing is a critical part of thruster life validation activities under NASA s Evolutionary Xenon Thruster (NEXT) project testing. The high voltage propellant isolators were selected for design verification testing. Even though they are based on a heritage design, design changes were made because the isolators will be operated under different environmental conditions including temperature, voltage, and pressure. The life test of two NEXT isolators was therefore initiated and has accumulated more than 10,000 hr of operation. Measurements to date indicate only a negligibly small increase in leakage current. The cathode heaters were also selected for verification testing. The technology to fabricate these heaters, developed for the International Space Station plasma contactor hollow cathode assembly, was transferred to Aerojet for the fabrication of the NEXT prototype model ion thrusters. Testing the contractor-fabricated heaters is necessary to validate fabrication processes for high reliability heaters. This paper documents the status of the propellant isolator and cathode heater tests.

Pinero, Luis R.↗

Verification of Software: The Textbook and Real Problems

The process of verification, or determining the order of accuracy of computational codes, can be problematic when working with large, legacy computational methods that have been used extensively in industry or government. Verification does not ensure that the computer program is producing a physically correct solution, it ensures merely that the observed order of accuracy of solutions are the same as the theoretical order of accuracy. The Method of Manufactured Solutions (MMS) is one of several ways for determining the order of accuracy. MMS is used to verify a series of computer codes progressing in sophistication from "textbook" to "real life" applications. The degree of numerical precision in the computations considerably influenced the range of mesh density to achieve the theoretical order of accuracy even for 1-D problems. The choice of manufactured solutions and mesh form shifted the observed order in specific areas but not in general. Solution residual (iterative) convergence was not always achieved for 2-D Euler manufactured solutions. L(sub 2,norm) convergence differed variable to variable therefore an observed order of accuracy could not be determined conclusively in all cases, the cause of which is currently under investigation.

Carlson, Jan-Renee↗

Verification and Planning Based on Coinductive Logic Programming

Coinduction is a powerful technique for reasoning about unfounded sets, unbounded structures, infinite automata, and interactive computations [6]. Where induction corresponds to least fixed point's semantics, coinduction corresponds to greatest fixed point semantics. Recently coinduction has been incorporated into logic programming and an elegant operational semantics developed for it [11, 12]. This operational semantics is the greatest fix point counterpart of SLD resolution (SLD resolution imparts operational semantics to least fix point based computations) and is termed co- SLD resolution. In co-SLD resolution, a predicate goal p( t) succeeds if it unifies with one of its ancestor calls. In addition, rational infinite terms are allowed as arguments of predicates. Infinite terms are represented as solutions to unification equations and the occurs check is omitted during the unification process. Coinductive Logic Programming (Co-LP) and Co-SLD resolution can be used to elegantly perform model checking and planning. A combined SLD and Co-SLD resolution based LP system forms the common basis for planning, scheduling, verification, model checking, and constraint solving [9, 4]. This is achieved by amalgamating SLD resolution, co-SLD resolution, and constraint logic programming [13] in a single logic programming system. Given that parallelism in logic programs can be implicitly exploited [8], complex, compute-intensive applications (planning, scheduling, model checking, etc.) can be executed in parallel on multi-core machines. Parallel execution can result in speed-ups as well as in larger instances of the problems being solved. In the remainder we elaborate on (i) how planning can be elegantly and efficiently performed under real-time constraints, (ii) how real-time systems can be elegantly and efficiently model- checked, as well as (iii) how hybrid systems can be verified in a combined system with both co-SLD and SLD resolution. Implementations of co-SLD resolution as well as preliminary implementations of the planning and verification applications have been developed [4]. Co-LP and Model Checking: The vast majority of properties that are to be verified can be classified into safety properties and liveness properties. It is well known within model checking that safety properties can be verified by reachability analysis, i.e, if a counter-example to the property exists, it can be finitely determined by enumerating all the reachable states of the Kripke structure.

Bansal, Ajay↗