Exhaustive Verification Research Articles

Formal Modeling and Verification of Lycklama and Hadzilacos’s Mutual Exclusion Algorithm

This study describes our thorough experience of formal modeling and exhaustive verification of concurrent systems, particularly mutual exclusion algorithms. The experience focuses on Lycklama and Hadzilacos’s (LH) mutual exclusion algorithm. LH rests on the reduced size of the shared state, contains a mechanism that tries to enforce an FCFS order to processes entering their critical section, and embodies Burns and Lamport’s (BL) mutual exclusion algorithm. The modeling methodology is based on timed automata and the model checker of the popular Uppaal toolbox. The effectiveness of the modeling and analysis approach is first demonstrated by studying the BL’s solution and retrieving all its properties, including, in general, its unbounded overtaking, which is the non-limited number of by-passes a process can suffer before accessing its critical section. Then, the LH algorithm is investigated in depth by showing it fulfills all the mutual exclusion properties when it operates with atomic memory. However, as this study demonstrates, LH is not free of deadlocks when used with non-atomic memory. Finally, a state-of-the-art mutual exclusion solution is proposed, which relies on a stripped-down LH version for processes, which is used as the arbitration unit in a tournament tree (TT) organization. This study documents that LH’s TT-based algorithm satisfies all the mutual exclusion properties, with a linear overtaking, both using atomic and non-atomic memory.

Introduction to the Special Issue on Runtime Verification

AbstractRuntime verification (RV) refers to methods for formal reasoning about all aspects of the dynamic execution of systems, including hardware, software, and cyber-physical systems. RV includes techniques to assess and enforce correctness of a system against systemic bugs or extrinsic uncertainties. These methods are typically considered lightweight as they may not involve exhaustive verification or proofs, but they provide a higher level of rigor and versatility compared to conventional testing methods. This article introduces the extended versions of selected papers from the peer-reviewed proceedings of the 20th International Conference on Runtime Verification (RV 2020). RV 2020 was supposed to be held in Los Angeles, California, USA in July 2020, but was instead held virtually due to the global Covid-19 pandemic.

From centralized to ad-hoc knowledge base construction for hypotheses generation

ObjectiveTo demonstrate and develop an approach enabling individual researchers or small teams to create their own ad-hoc, lightweight knowledge bases tailored for specialized scientific interests, using text-mining over scientific literature, and demonstrate the effectiveness of these knowledge bases in hypothesis generation and literature-based discovery (LBD). MethodsWe propose a lightweight process using an extractive search framework to create ad-hoc knowledge bases, which require minimal training and no background in bio-curation or computer science. These knowledge bases are particularly effective for LBD and hypothesis generation using Swanson's ABC method. The personalized nature of the knowledge bases allows for a somewhat higher level of noise than “public facing” ones, as researchers are expected to have prior domain experience to separate signal from noise. Fact verification is shifted from exhaustive verification of the knowledge base to post-hoc verification of specific entries of interest, allowing researchers to assess the correctness of relevant knowledge base entries by considering the paragraphs in which the facts were introduced. ResultsWe demonstrate the methodology by constructing several knowledge bases of different kinds: three knowledge bases that support lab-internal hypothesis generation: Drug Delivery to Ovarian Tumors (DDOT); Tissue Engineering and Regeneration; Challenges in Cancer Research; and an additional comprehensive, accurate knowledge base designated as a public resource for the wider community on the topic of Cell Specific Drug Delivery (CSDD). In each case, we show the design and construction process, along with relevant visualizations for data exploration, and hypothesis generation. For CSDD and DDOT we also show meta-analysis, human evaluation, and in vitro experimental evaluation. ConclusionOur approach enables researchers to create personalized, lightweight knowledge bases for specialized scientific interests, effectively facilitating hypothesis generation and literature-based discovery (LBD). By shifting fact verification efforts to post-hoc verification of specific entries, researchers can focus on exploring and generating hypotheses based on their expertise. The constructed knowledge bases demonstrate the versatility and adaptability of our approach to versatile research interests. The web-based platform, available at https://spike-kbc.apps.allenai.org, provides researchers with a valuable tool for rapid construction of knowledge bases tailored to their needs.

A grasp planning algorithm under uneven contact point distribution scenario for space non-cooperative target capture

The contact point configuration should be carefully chosen to ensure a stable capture, especially for the non-cooperative target capture mission using multi-armed spacecraft. In this work scenario, the contact points on the base and on the arms are distributed on the opposite side of the target. Otherwise, large forces will be needed. To cope with this problem, an uneven-oriented distribution union criterion is proposed. The union criterion contains a virtual symmetrical criterion and a geometry criterion. The virtual symmetrical contact point criterion is derived from the proof of the force closure principle using computational geometry to ensure a stable grasp, and the geometry criterion is calculated by the volume of the minimum polyhedron formed by the contact points to get a wide-range distribution. To further accelerate the optimization rate and enhance the global search ability, a line array modeling method and a continuous-discrete global search algorithm are proposed. The line array modeling method reduces the workload of calculating the descent direction and the gradient available, while the continuous-discrete global search algorithm reducing the optimization dimension. Then a highly efficient grasping is achieved and the corresponding contact point is calculated. Finally, an exhaustive verification is conducted to numerically analyze the disturbance resistance ability, and simulation results demonstrate the effectiveness of the proposed algorithms.

ActivFORMS: A Formally Founded Model-based Approach to Engineer Self-adaptive Systems

Self-adaptation equips a computing system with a feedback loop that enables it to deal with change caused by uncertainties during operation, such as changing availability of resources and fluctuating workloads. To ensure that the system complies with the adaptation goals, recent research suggests the use of formal techniques at runtime. Yet, existing approaches have three limitations that affect their practical applicability: (i) they ignore correctness of the behavior of the feedback loop, (ii) they rely on exhaustive verification at runtime to select adaptation options to realize the adaptation goals, which is time- and resource-demanding, and (iii) they provide limited or no support for changing adaptation goals at runtime. To tackle these shortcomings, we present ActivFORMS (Active FORmal Models for Self-adaptation). ActivFORMS contributes an end-to-end approach for engineering self-adaptive systems, spanning four main stages of the life cycle of a feedback loop: design, deployment, runtime adaptation, and evolution. We also present ActivFORMS-ta, a tool-supported instance of ActivFORMS that leverages timed automata models and statistical model checking at runtime. We validate the research results using an IoT application for building security monitoring that is deployed in Leuven. The experimental results demonstrate that ActivFORMS supports correctness of the behavior of the feedback loop, achieves the adaptation goals in an efficient way, and supports changing adaptation goals at runtime.

A hybrid model for efficient decision-making in self-adaptive systems

Engineering self-adaptive systems to guarantee the required quality properties is challenging and particularly in presence of uncertainties. Such uncertainties may occur in a variety of situations, ranging from variations in the system’s operating environment to ambiguity while selecting the appropriate adaptation option. Formal methods provide a rigorous means to specify and verify the behavior of self-adaptive systems. They are applied both during system design and at runtime to provide guarantees on the required properties of self-adaptive systems. However, existing approaches generally use exhaustive verification at runtime to pick adaptation options and achieve adaptation objectives, which is time and resource consuming. Aiming to tackle this shortcoming, we target a twofold objective. Firstly, we reduce the adaptation space, and then we predict the impact of each adaptation plan on the rest of system qualities, to assist the decision-making process in determining the most suitable adaptation plans and side effects. An Adaptation-space Reducer component is added to the analyser element; it uses deep learning to reduce the adaptation space. Furthermore, the planner element has been extended with a Decision Impact Predictor component, which employs quantitative analysis to forecast the impact of a decision. The DLA4EDM is defined as an approach for providing self-adaptive systems (SASs) with an efficient decision-making process. Our approach is applied on a self-adaptive Internet of Things application and the obtained results are compared to those of other approaches. Results show that the adaptation space is reduced by 97.57%, and the error rate in the decision-making is very low. Reducing the adaptation space and resolving uncertainties to be faced in the decision-making of self-adaptive systems contribute considerably to enhance the efficiency and quality of the adaptation process and hence ensure that the quality requirements are met. Evaluating the impact of the identified adaptation plans on the obtained guarantees ensures that the system is effectively operational.

Incremental constraint-based reasoning for estimating as-built electric line routing in buildings

This article addresses the augmentation of existing building models by a priori not observable structures such as electric installations. The aim is to unambiguously determine an electric network in an incremental manner with a minimum number of local measurements, e.g. using wire detectors, by suggesting the next measurement. Different reasoning strategies, e.g. utilizing graph-theoretical algorithms, have been presented and tested based on a hypothesis which is generated using Mixed Integer Linear Programming (MILP) while incorporating standards regarding the installation of electric wiring and findings from previous measurements. The presented method has been successfully applied on simulated and real-world buildings, it saves up to 80% of the necessary measurements compared to an exhaustive verification of the whole existing electric network, and paves the way for efficiently extending existing models, e.g. GIS models, with information on hidden utilities. This opens up new opportunities to model further infrastructures, e.g. water pipes, in future research.

Hybrids acceptance tools for the CMS Phase-2 Tracker Upgrade

Up to fifty thousand front-end and service hybrids are required for the CMS Outer Tracker Phase-2 Upgrade. These hybrids, which are built on carbon fibre stiffened circuits and contain several flip-chip ASICs, will be glued in module structures, making repairs almost impossible. Due to their complexity, testing within production is a very important aspect. A multiplexed testing infrastructure, based on custom crates and test cards, is presented. This testing hardware is supported by software tools to enable the exhaustive verification of hybrids at the manufacturing sites and for their acceptance within the collaboration.

Multidimensional Numerical Modeling of Combustion Dynamics in a Non-Premixed Rotating Detonation Engine With Adaptive Mesh Refinement

Abstract In the present work, a novel computational fluid dynamics (CFD) methodology was developed to simulate full-scale non-premixed rotating detonation engines (RDEs). A unique feature of the modeling approach was the incorporation of adaptive mesh refinement (AMR) to achieve a good trade-off between model accuracy and computational expense. Unsteady Reynolds-averaged Navier–Stokes (RANS) simulations were performed for an Air Force Research Laboratory (AFRL) non-premixed RDE configuration with hydrogen as fuel and air as the oxidizer. The finite-rate chemistry model, along with a ten-species detailed kinetic mechanism, was employed to describe the H2-Air combustion chemistry. Three distinct operating conditions were simulated, corresponding to the same global equivalence ratio of unity but different fuel/air mass flowrates. For all conditions, the capability of the model to capture essential detonation wave dynamics was assessed. An exhaustive verification and validation study was performed against experimental data in terms of a number of waves, wave frequency, wave height, reactant fill height, oblique shock angle, axial pressure distribution in the channel, and fuel/air plenum pressure. The CFD model was demonstrated to accurately predict the sensitivity of these wave characteristics to the operating conditions, both qualitatively and quantitatively. A comprehensive heat release analysis was also conducted to quantify detonative versus deflagrative burning for the three simulated cases. The present CFD model offers a potential capability to perform rapid design space exploration and/or performance optimization studies for realistic full-scale RDE configurations.

Formal Modeling, Proving, and Model Checking of a Flood Warning, Monitoring, and Rescue System-of-Systems

Floods after monsoon rains are frequent disasters that affect millions of lives in Pakistan. Human lives are lost, agriculture economies are destroyed, and livestock animals, houses, fruit farms, and crops are lost which are the major livelihoods of thousands of people in Punjab. Each year there are heavy rains in the monsoon season and, due to global warming, there is the rapid melting of snow in northern glaciers; these factors subsequently cause floods. There is also loss of life due to the spread of waterborne diseases and snake bites. Flood monitoring provides early detection of a flood and the calculation of its intensity, which results in reduced human life losses and economic losses. Most casualties are caused by the lack of timely real-time, authentic information about the high-risk areas, and flood intensity, speed, and direction. Therefore, the proposed approach is centered on formal modeling and verification of safety and liveness properties of flood monitoring perceivers. Each flood perceiver has several sensors. It requires the collection of information starting from the flood perceiver, observer, and environmental forecast. This information is processed to determine the flood intensity level. We have developed a CP-Nets’ formal model and model-checked it. We have verified the safety and liveness properties of correctness by exhaustive verification of the system using model-based proof obligations (Event-B method using Rodin). Our objective in this research is to propose a correct, reliable, and efficient flood warning, monitoring, and rescue (WMR) SoS based on formal methods. We have used formal modeling and model-checking based on state-of-the-art hierarchical CP-Nets supported by exhaustive formal proof obligations of Event-B.

Lazy Repairing Backtracking for Dynamic Constraint Satisfaction Problems

Extended Partial Dynamic Backtracking (EPDB) is a repair algorithm based on PDB. It deals with Dynamic CSPs based on ordering heuristics and retroactive data structures, safety conditions, and nogoods which are saved during the search process. In this paper, we show that the drawback of both EPDB and PDB is the exhaustive verification of orders, saved in safety conditions and nogoods, between variables. This verification affects remarkably search time, especially since orders are often indirectly deduced. Therefore, we propose a new approach for dynamically changing environments, the Lazy Repairing Backtracking (LRB), which is a fast version of EPDB insofar as it deduces orders directly through the used ordering heuristic. We evaluate LRB on various kinds of problems, and compare it, on the one hand, with EPDB to show its effectiveness compared to this approach, and, on the other hand, with MAC-2001 in order to conclude, from what perturbation rate resolving a DCSP with an efficient approach can be more advantageous than repair.

A Distributed Hardware Monitoring System for Runtime Verification on Multi-Tile MPSoCs

Exhaustive verification techniques do not scale with the complexity of today’s multi-tile Multi-processor Systems-on-chip (MPSoCs). Hence, runtime verification (RV) has emerged as a complementary method, which verifies the correct behavior of applications executed on the MPSoC during runtime. In this article, we propose a decentralized monitoring architecture for large-scale multi-tile MPSoCs. In order to minimize performance and power overhead for RV, we propose a lightweight and non-intrusive hardware solution. It features a new specialized tracing interconnect that distributes and sorts detected events according to their timestamps. Each tile monitor has a consistent view on a globally sorted trace of events on which the behavior of the target application can be verified using logical and timing requirements. Furthermore, we propose an integer linear programming-based algorithm for the assignment of requirements to monitors to exploit the local resources best. The monitoring architecture is demonstrated for a four-tiled MPSoC with 20 cores implemented on a Virtex-7 field-programmable gate array (FPGA).

Steerable High-Gain Dual-Reflector Antenna at X-Band for Solar Orbiter

This article presents the design, optimization, analysis, and test of a dual-axis steerable X-band dual-reflector antenna for Solar Orbiter. The system is a part of the onboard antenna subsystem of the Solar Orbiter probe, a science mission from the European Space Agency (ESA) whose goal is to study the Sun and its heliosphere. From the engineering point of view, it is remarkably the extremely harsh orbit environmental conditions. The presented high-gain antenna must operate within a thermal range from -200 °C to 580 °C. To withstand such constraints, the design of the dual-reflector system is optimized considering the thermal distortions imposed by the environment, yielding the final design whose radio frequency (RF) performances are marginally impacted during the different orbit conditions and phases of the mission. An exhaustive verification campaign is also performed to test the antenna under nearly orbit environment.

Modelling and Verifying Dynamic Access Control Policies in Workflow-Based Healthcare Systems

Access control system is an important component to protect patients’ information from abuse in a health care system. It is a major concern in the management, design, and development of healthcare systems. Designing access control policies for healthcare systems is complicated due to the dynamic and inherent complexity of the tasks performed by the healthcare personnel. Permissions in access control systems are usually granted on the basis of static policies. However, static policies are not enough to cope with various situations such as emergencies. Most often, the Break-the-glass mechanism is used to bypass static policies to handle emergency situations. Since healthcare systems are critical systems, where errors can be very costly in terms of lives, quality of life, and/or dollars, it is crucial to identify discrepancies between policy specifications and their intended function to implement correctly a flexible access control system. Formal verifications are necessary for exhaustive verification and validation of policy specifications to ensure that the policy specifications truly encapsulate the desires of the policy authors. We present a verifiable framework to enact a dynamic access control model by integrating the ANSI/INCTIS RBAC Reference Model in a workflow and an approach for property verifications of the access control model. Access control policies are expressed by the formal semantics of a model checker and properties are verified by the DiVinE model checker.

Formal reasoning on knowledge and commitments in multi-agent systems using Theatre

This paper proposes a formal method based on the Theatre framework for modeling and analysis of knowledge and commitments in multi-agent systems (MASs). Theatre centers on actors and a reduction on to Uppaal, which enables both non-deterministic analysis (that is, qualitative analysis by exhaustive verification, or showing that something can possibly occur) and quantitative analysis (that is, estimating probability measures of event occurrence through simulations) of the same model. The article describes the modeling and analysis approach based on Theatre and Uppaal, and shows its application to the modeling and property checking of the NetBill protocol used in web-based MAS applications when selling/buying goods. Properties of the NetBill protocol are demonstrated by experimental results.

A Simulation Environment for Validation and Verification of Real Time Hyperspectral Processing Algorithms on-Board a UAV

The utilization of hyperspectral imaging sensors has gained a significant relevance among many different applications due to their capability for collecting a huge amount of information across the electromagnetic spectrum. These sensors have been traditionally mounted on-board satellites and airplanes in order to extract information from the Earth’s surface. Fortunately, the progressive miniaturization of these sensors during the last lustrum has enabled their use in other remote sensing platforms, such as drones equipped with hyperspectral cameras which bring advantages in terms of higher spatial resolution of the acquired images, more flexible revisit times and lower cost of the flight campaigns. However, when these drones are autonomously flying and taking real-time critical decisions from the information contained in the captured images, it is crucial that the whole process takes place in a safe and predictable manner. In order to deal with this problem, a simulation environment is presented in this work to analyze the virtual behavior of a drone equipped with a pushbroom hyperspectral camera used for assisting harvesting applications, which enables an exhaustive and realistic validation and verification of the drone real-time hyperspectral imaging system prior to its launch. To the best of the authors’ knowledge, the proposed environment represents the only solution in the state-of-the-art that allows the virtual verification of real-time hyperspectral image processing algorithms under realistic conditions.

Simplified CFD model of coolant channels typical of a plate-type fuel element: an exhaustive verification of the simulations

The use of parallel plate-type fuel assemblies is common in nuclear research reactors. One of the main problems of this fuel element configuration is the hydroelastic instability of the plates caused by the high flow velocities. The current work is focused on the hydrodynamic characterization of coolant channels typical of a flat-plate fuel element, using a numerical model developed with the commercial code ANSYS CFX. Numerical results are compared to accurate analytical solutions, considering two turbulence models and three different fluid meshes. For this study, the results demonstrated that the most suitable turbulence model is the k-e model. The discretization error is estimated using the Grid Convergence Index method. Despite its simplicity, this model generates precise flow predictions.

Sensorless full body active compliance in a 6 DOF parallel manipulator

• Interpretation of the torque data at actuated joints allowing it to comply to a force at any point of the manipulator. • 3-layer cascaded impedance control which maintains the accuracy of trajectory tracking while making the manipulator inherently compliant. • Comparison of the dynamic performances depending on the choice of topology of the manipulator. • Exhaustive verification of the data using well calibrated tools such as Vicon ® and Bertec ® . Parallel manipulators are being used extensively to cater to the needs of a multitude of industrial automation applications. Due to its kinematic accuracy and structural stiffness , parallel manipulators have proven considerable advantage over their serial counterparts. In modern applications, humans train, collaborate and interact with the manipulators in order to maximize the productivity and the quality of the final product. The critical factor in this human-robot interaction is safety and the ability of the mechanism to comply with human intentions. It thus becomes a necessity for the manipulator to detect external disturbances and interactions, and be able to react accordingly. In this research, a methodology for sensor-less full body active compliance is proposed on a 6-DOF RSS (Rotary-Spherical-Spherical) parallel manipulator. By using the proposed approach, the manipulator can detect and comply with the external forces on any part of its body without using any explicit force/torque sensor at the joint or the end-effector. This is done by utilizing the estimated joint torque based on the actuator current feedback only. A three-layer cascaded impedance controller for active compliance and reaction to various human interactions are reported. The proposed design and unique methodology for compliance exhibits an effective and inexpensive yet reliable alternative to be used in safe human-robot interactions and force controlled manufacturing applications.

Gestión de control patrimonial y su influencia en las altas y bajas de bienes muebles del Gobierno Regional de Tacna, periodo 2016

El presente trabajo de investigación, reúne los diferentes aspectos de la gestión de control patrimonial las mismas que influyen en las altas y bajas de los bienes muebles del Gobierno Regional de Tacna, en el periodo 2016; así mismo se recopiló información de procedimientos, registro y control de bienes, coordinación y supervisión, normas y directivas establecidas por la entidad del Gobierno Regional de Tacna. El trabajo que se desarrolló es no experimental, descriptivo y correlacional de acuerdo a la finalidad de la investigación. El área de investigación está enmarcada en la contabilidad gubernamental, debido a que es una actividad encaminada al análisis y la evaluación de los procedimientos, alta y baja de bienes muebles para una buena gestión de control patrimonial, a través de la evaluación de la eficiencia, eficacia, economía de la Entidad. La institución materia de estudio tiene deficiencias en el control de inventario esto se debe a que se recibe los inventarios físicos sin ser constatados con una verificación exhaustiva, así como los bienes que se encuentran obsoletos por los cambios tecnológicos, no teniendo una cantidad exacta de los bienes patrimoniales que están bajo la administración de la institución, así como personal no capacitado.

System-level state equality detection for the formal dynamic verification of legacy distributed applications

The ever increasing complexity of distributed systems mandates to formally verify their design and implementation. Unfortunately, the common approaches and existing tools to formally establish the correctness of these systems remain hardly applicable to most legacy HPC applications, that are commonly written in Fortran or C/C++, using the MPI standard.This work addresses the problem of automatically detecting at system-level the equality of the application's state. This allows to automatically verify safety and liveness properties on legacy HPC applications. We present how this state equality detection can be achieved without any source code static analysis, but at runtime using memory introspection and classical debugging techniques.We demonstrate the effectiveness of our approach through the exhaustive verification of several programs from the MPICH3 test suite and through the partial termination analysis of some applications from the Competition on Software Verification (SV-COMP).