Safety Verification of Fault Tolerant Goal-based Control Programs with Estimation Uncertainty

Fault tolerance and safety verification of control systems that have state variable estimation uncertainty are essential for the success of autonomous robotic systems. A software control architecture called mission data system, developed at the Jet Propulsion Laboratory, uses goal networks as the control program for autonomous systems. Certain types of goal networks can be converted into linear hybrid systems and verified for safety using existing symbolic model checking software. A process for calculating the probability of failure of certain classes of verifiable goal networks due to state estimation uncertainty is presented. A verifiable example task is presented and the failure probability of the control program based on estimation uncertainty is found

Comparison of 2D grid simulations for flow past cylinder at high Reynolds numbers

The paper focuses on the verification of the suitability of the SST k - omega model on the flow past a circular cylinder in 2D for a high Reynolds number. The study compares the results of drag and lifts coefficients with respect to different types of meshes and time steps. The mean velocity field in the wake region behind the cylinder is evaluated and compared to experimental data available from literature. The numerical simulations are solved using CFD codes in the ANSYS Fluent software and use the finite volume method.Web of Science151787

On Deciding Local Theory Extensions via E-matching

Satisfiability Modulo Theories (SMT) solvers incorporate decision procedures for theories of data types that commonly occur in software. This makes them important tools for automating verification problems. A limitation frequently encountered is that verification problems are often not fully expressible in the theories supported natively by the solvers. Many solvers allow the specification of application-specific theories as quantified axioms, but their handling is incomplete outside of narrow special cases. In this work, we show how SMT solvers can be used to obtain complete decision procedures for local theory extensions, an important class of theories that are decidable using finite instantiation of axioms. We present an algorithm that uses E-matching to generate instances incrementally during the search, significantly reducing the number of generated instances compared to eager instantiation strategies. We have used two SMT solvers to implement this algorithm and conducted an extensive experimental evaluation on benchmarks derived from verification conditions for heap-manipulating programs. We believe that our results are of interest to both the users of SMT solvers as well as their developers

Solving the Partial Differential Problems Using Maple

AbstractThis paper considers the partial differential problem of two types of multivariable functions and uses mathematical software Maple for verification. The infinite series forms of any order partial derivatives of these two types of multivariable functions can be obtained using binomial series and differentiation term by term theorem, which greatly reduce the difficulty of calculating their higher order partial derivative values. On the other hand, four examples are used to demonstrate the calculations

A Domain Specific Language Based Approach for Generating Deadlock-Free Parallel Load Scheduling Protocols for Distributed Systems

In this dissertation, the concept of using domain specific language to develop errorree parallel asynchronous load scheduling protocols for distributed systems is studied. The motivation of this study is rooted in addressing the high cost of verifying parallel asynchronous load scheduling protocols. Asynchronous parallel applications are prone to subtle bugs such as deadlocks and race conditions due to the possibility of non-determinism. Due to this non-deterministic behavior, traditional testing methods are less effective at finding software faults. One approach that can eliminate these software bugs is to employ model checking techniques that can verify that non-determinism will not cause software faults in parallel programs. Unfortunately, model checking requires the development of a verification model of a program in a separate verification language which can be an error-prone procedure and may not properly represent the semantics of the original system. The model checking approach can provide true positive result if the semantics of an implementation code and a verification model is represented under a single framework such that the verification model closely represents the implementation and the automation of a verification process is natural. In this dissertation, a domain specific language based verification framework is developed to design parallel load scheduling protocols and automatically verify their behavioral properties through model checking. A specification language, LBDSL, is introduced that facilitates the development of parallel load scheduling protocols. The LBDSL verification framework uses model checking techniques to verify the asynchronous behavior of the protocol. It allows the same protocol specification to be used for verification and the code generation. The support to automatic verification during protocol development reduces the verification cost post development. The applicability of LBDSL verification framework is illustrated by performing case study on three different types of load scheduling protocols. The study shows that the LBDSL based verification approach removes the need of debugging for deadlocks and race bugs which has potential to significantly lower software development costs

Generic Methodology for Formal Verification of UML Models

This paper discusses a Unified Modelling Language (UML) based formal verification methodology for early error detection in the model-based software development cycle. Our approach proposes a UML-based formal verification process utilising functional and behavioural modelling artifacts of UML. It reinforces these artifacts with formal model transition and property verification. The main contribution is a UML to Labelled Transition System (LTS) Translator application that automatically converts UML Statecharts to formal models. Property specifications are derived from system requirements and corresponding Computational Tree Logic (CTL)/Linear Temporal Logic (LTL) model checking procedure verifies property entailment in LTS. With its ability to verify CTL and LTL specifications, the methodology becomes generic for verifying all types of embedded system behaviours. The steep learning curve associated with formal methods is avoided through the automatic formal model generation and thus reduces the reluctance of using formal methods in software development projects. A case study of an embedded controller used in military applications validates the methodology. It establishes how the methodology finds its use in verifying the correctness and consistency of UML models before implementation

Dosimetric validation for an automatic brain metastases planning software using single-isocenter dynamic conformal arcsDosimetric validation for an automatic brain metastases planning software using single-isocenter dynamic conformal arcs.

An automatic brain-metastases planning (ABMP) software has been installed in our institution. It is dedicated for treating multiple brain metastases with radiosurgery on linear accelerators (linacs) using a single-setup isocenter with noncoplanar dynamic conformal arcs. This study is to validate the calculated absolute dose and dose distribution of ABMP. Three types of measurements were performed to validate the planning software: 1, dual micro ion chambers were used with an acrylic phantom to measure the absolute dose; 2, a 3D cylindrical phantom with dual diode array was used to evaluate 2D dose distribution and point dose for smaller targets; and 3, a 3D pseudo-in vivo patient-specific phantom filled with polymer gels was used to evaluate the accuracy of 3D dose distribution and radia-tion delivery. Micro chamber measurement of two targets (volumes of 1.2 cc and 0.9 cc, respectively) showed that the percentage differences of the absolute dose at both targets were less than 1%. Averaged GI passing rate of five different plans measured with the diode array phantom was above 98%, using criteria of 3% dose difference, 1 mm distance to agreement (DTA), and 10% low-dose threshold. 3D gel phantom measurement results demonstrated a 3D displacement of nine targets of 0.7 ± 0.4 mm (range 0.2 ~ 1.1 mm). The averaged two-dimensional (2D) GI passing rate for several region of interests (ROI) on axial slices that encompass each one of the nine targets was above 98% (5% dose difference, 2 mm DTA, and 10% low-dose threshold). Measured D95, the minimum dose that covers 95% of the target volume, of the nine targets was 0.7% less than the calculated D95. Three different types of dosimetric verification methods were used and proved the dose calculation of the new automatic brain metastases planning (ABMP) software was clinical acceptable. The 3D pseudo-in vivo patient-specific gel phantom test also served as an end-to-end test for validating not only the dose calculation, but the treatment delivery accuracy as well

Chemical-Based Formulation Design: Virtual Experimentation

This paper presents a software, the virtual Product-Process Design laboratory (virtual PPD-lab) and the virtual experimental scenarios for design/verification of consumer oriented liquid formulated products where the software can be used. For example, the software can be employed for the design of the active ingredient-solvent mixture and/or their verification in terms of the product function. These consumer products are still primarily designed, developed and/or tested through experiment-based trial and error approaches. However, using the powerful methodologies and tools developed within the process system engineering community, it is possible now to replace, at least, some of the experimental steps with efficient and validated model-based approaches. For example, the search space can be significantly reduced through computer-aided screenings of the active ingredient (AI), the solvent mixture, the additives and/or their mixtures (formulations). Therefore, the experimental resources can focus on a few candidate product formulations to find the best product. The virtual PPD-lab allows various options for experimentations related to design and/or verification of the product. For example, the selection and verification of the functions of the AI; the design of solvent mixtures for the delivery of the AI; the stability test of the liquid formulated product; the selection of additives such as aroma compounds to be added to the products to enhance their quality; the generation of a list of candidate formulations; the addition of the missing chemicals to an incomplete formulation and the verification of the final product. The software is based on a framework that allows quick implementation of different design/verification work-flows and their associated models, methods, tools and data. The software contains a suite of databases with data of AIs used in different products (such as insect repellents), solvents classified in terms of special characteristics (such as solubility in water), and additives classified in terms of their application (such as aroma agents, wetting agents and preservatives). In addition, the software has built-in intelligence through implemented knowledge-bases related to transforming product attributes (consumer needs) to a set of physical-chemical properties; templates (work-flows) for specific product types are also available; guidance for property model (such as pure component properties and mixture properties) selection and adaptation is provided; the selection and use of models for product verification is also possible (such as stability of liquid and evaporation of the solvent after application of the product). Finally, the software has a collection of algorithms (such as CAMD, mixture design, model adaptation). All of the above helps to perform virtual experiments by blending chemicals together and observing their predicted behaviour. The paper will highlight the application of the virtual PPD-lab in the design and/or verification of different consumer products (paint formulation, hair spray, sunscreen lotion, insect repellent lotion). The results of the virtual experimentations will be illustrated through the (initial) base case designs that were obtained and their verification through real experiments and/or available product data analysis

Cross-platform verification framework for embedded systems

Many innovations in the automotive sector involve complex electronics and embedded software systems. Testing techniques are one of the key methodologies for detecting faults in such embedded systems.In this paper, a novel cross-platform verification framework including automated test-case generation by model checking is introduced. Comparing the execution behavior of a program instance running on a certain platform to the execution behavior of the same program running on a different platform we denote cross-platform verification. The framework supports various types of coverage criteria. It turned out that end-to-end testing is of high importance due to defects occurring on the actual target platform for the first time.Additionally, formal verification can be applied for checking requirements resulting from the specification using the same model generation mechanism that is used for test data generation. Due to a novel self-assessment mechanism, the confidence into the formal models is increased significantly.We provide a case study for the Motorola embedded controller HCS12 that is heavily used by the automotive industry. We perform structural tests on industrial code patterns using a wide-spread industrial compiler. Using our technique, we found two severe compiler defects that have been corrected in subsequent releases