Enhancing Temporal Logic Falsification of Cyber-Physical Systems using multiple objective functions and a new optimization method

Cyber-physical systems (CPSs) are engineering systems that bridge the cyber-world of communications and computing with the physical world. These systems are usually safety-critical and exhibit both discrete and continuous dynamics that may have complex behavior. Typically, these systems have to satisfy given specifications, i.e., properties that define the valid behavior. One commonly used approach to evaluate the correctness of CPSs is testing. The main aim of testing is to detect if there are situations that may falsify the specifications.\ua0For many industrial applications, it is only possible to simulate the system under test because mathematical models do not exist, thus formal verification is not a viable option. Falsification is a strategy that can be used for testing CPSs as long as the system can be simulated and formal specifications exist. Falsification attempts to find counterexamples, in the form of input signals and parameters, that violate the specifications of the system. Random search or optimization can be used for the falsification process. In the case of an optimization-based approach, a quantitative semantics is needed to associate a simulation with a measure of the distance to a specification being falsified. This measure is used to guide the search in a direction that is more likely to falsify a specification, if possible. \ua0The measure can be defined in different ways. In this thesis, we evaluate different quantitative semantics that can be used to define this measure. The efficiency of the falsification can be affected by both the quantitative semantics used and the choice of the optimization method. The presented work attempts to improve the efficiency of the falsification process by suggesting to use multiple quantitative semantics, as well as a new optimization method. The use of different quantitative semantics and the new optimization method have been evaluated on standard benchmark problems. We show that the proposed methods improve the efficiency of the falsification process

On Optimization-Based Falsification of Cyber-Physical Systems

In what is commonly referred to as cyber-physical systems (CPSs), computational and physical resources are closely interconnected. An example is the closed-loop behavior of perception, planning, and control algorithms, executing on a computer and interacting with a physical environment. Many CPSs are safety-critical, and it is thus important to guarantee that they behave according to given specifications that define the correct behavior. CPS models typically include differential equations, state machines, and code written in general-purpose programming languages. This heterogeneity makes it generally not feasible to use analytical methods to evaluate the system’s correctness. Instead, model-based testing of a simulation of the system is more viable. Optimization-based falsification is an approach to, using a simulation model, automatically check for the existence of input signals that make the CPS violate given specifications. Quantitative semantics estimate how far the specification is from being violated for a given scenario. The decision variables in the optimization problems are parameters that determine the type and shape of generated input signals. This thesis contributes to the increased efficiency of optimization-based falsification in four ways. (i) A method for using multiple quantitative semantics during optimization-based falsification. (ii) A direct search approach, called line-search falsification that prioritizes extreme values, which are known to often falsify specifications, and has a good balance between exploration and exploitation of the parameter space. (iii) An adaptation of Bayesian optimization that allows for injecting prior knowledge and uses a special acquisition function for finding falsifying points rather than the global minima. (iv) An investigation of different input signal parameterizations and their coverability of the space and time and frequency domains. The proposed methods have been implemented and evaluated on standard falsification benchmark problems. Based on these empirical studies, we show the efficiency of the proposed methods. Taken together, the proposed methods are important contributions to the falsification of CPSs and in enabling a more efficient falsification process

Technical Report: The effect of Input Parameters on Falsification of Cyber-Physical Systems

The aim of this technical report is to investigate the effect of input parameters on the falsification of cyber-physical systems (CPSs)

Cisplatin Nephrotoxicity and Protection by Milk Thistle Extract in Rats

The protective effect of methanolic extract of milk thistle seeds and silymarin against cisplatin-induced renal toxicity in male rats after a single intraperitoneal injection of 3 mg kg(−1) cisplatin were studied. Over 5 days, cisplatin-treated rats showed tubular necrosis and elevation in blood urea nitrogen (BUN) and serum creatinine (Scr). Pretreatment of animals with silymarin (50 mg kg(−1)) or extract (0.6 g kg(−1)) 2 h before cisplatin prevented the tubular damage. Rats treated with silymarin or extract 2 h after cisplatin had BUN and Scr significantly lower than those receiving cisplatin, but mild to moderate necrosis was observed. These results suggested that milk thistle may protect against cisplatin-induced renal toxicity and might serve as a novel combination agent with cisplatin to limit renal injury

Evaluating Two Semantics for Falsification using an Autonomous Driving Example

We consider the falsification of temporal logic properties as a method to test complex systems, such as autonomous systems. Since these systems are often safety-critical, it is important to assess whether they fulfill given specifications or not. An adaptive cruise controller for an autonomous car is considered where the closed-loop model has unknown parameters and an important problem is to find parameter combinations for which given specification are broken. We assume that the closed-loop system can be simulated with the known given parameters, no other information is available to the testing framework. The specification, such as, the ability to avoid collisions, is expressed using Signal Temporal Logic (STL). In general, systems consist of a large number of parameters, and it is not possible or feasible to explicitly enumerate all combinations of the parameters. Thus, an optimization-based approach is used to guide the search for parameters that might falsify the specification. However, a key challenge is how to select the objective function such that the falsification of the specification, if it can be falsified, can be falsified using as few simulations as possible. For falsification using optimization it is required to have a measure representing the distance to the falsification of the specification. The way the measure is defined results in different objective functions used during optimization. Different measures have been proposed in the literature and in this paper the properties of the Max Semantics (MAX) and the Mean Alternative Robustness Value (MARV) semantics are discussed. After evaluating these two semantics on an adaptive cruise control example, we discuss their strengths and weaknesses to better understand the properties of the two semantics

Temporal Logic Falsification of Cyber-Physical Systems using Input Pulse Generators

Falsification is a testing method for cyber-physical systems where numerical optimization is used to find counterexamples of a given specification that the system must fulfill. The falsification process uses quantitative semantics that play the role of objective functions to minimize the distance to falsifying the specification. Falsification has gained attention due to its versatile applicability, and much work exists on various ways of implementing the falsification process, often focusing on which optimization algorithm to use, or more recently, the semantics for the formal requirements. In this work, we look at some practical aspects of input generation, i.e., the mapping from parameters used as optimization variables to signals that form the actual test cases for the system. This choice is critical but often overlooked. It is assumed that problem experts can guide how to parameterize inputs; however, this assumption is often too optimistic in practice. We observe that pulse generation is a surprisingly good first option that can falsify many common benchmarks after only a few simulations while requiring only a few parameters per signal

Comparative Case Studies of Reactive Synthesis and Supervisory Control

Reactive Synthesis and Supervisory Control Theory are both systematic approaches for the automatic construction of controllers from requirements. However, their underlying technicalities differ significantly. This paper provides an empirical comparison between these two approaches from the modelling perspective through case studies. Using the synthesis tools TuLiP and Supremica, two examples are modelled in the typical modelling formalism supported by each tool, and the algorithms are applied to synthesize controllers. Based on the obtained models and experiences, we compare how the models are derived, and how the characteristics of the examples and the underlying synthesis algorithms influence the modelling choices

SARS-Cov2-Induced Cytokine Storm and Schizophrenia, Could There be a Connection?

Today, a new coronavirus (2019-nCoV, later named SARS-CoV-2) has become known as a pandemic with over 3,949,200 cases and 271,782 deaths. It has been considered that most of the deaths in infected patients stem from comorbidity conditions. Therefore, understanding at-risk populations are currently under the focus of investigations. This object has highly driven attention to put patients with a higher potential of death related to SARS-CoV2 infection at priority. For instance, this can happen in Schizophrenia owing to ambiguous immunology attributes, including elevated levels of pro-inflammatory cytokines and stress-related immune disability. Given that, the hyper-inflammatory responses are the significant cause of the pathophysiology of the SARS-CoV2-related mortality. Moreover, SARS-CoV2 can prompt the risk of developing Schizophrenia in the future. This review punctuates that prenatal/perinatal infection could be associated with increased Schizophrenia risk; on the flip side, the potential risk of ongoing medication can worsen mentally disabled patients, and healthy people are at risk

Adsorption of Alizarin Red S Dye on Raw Endoskeleton Nanopowder of Cuttlefish (Sepia Pharaonis) from Water Solutions: Mechanism, Kinetics and Equilibrium Modeling

The potential of the raw cuttlebone nano-powder (CBNP), a biomass waste, as a novel and nontoxic adsorbent for the adsorption of Alizarin Red S (ARS) from water solutions was investigated. To achieve the highest efficiency for the removal of ARS, some affecting factors were optimized. Common techniques (FTIR, FESEM, EDX and XRF) were used to characterize the physicochemical features of the adsorbent. Various kinetic and isotherm models were used to obtain the useful information about the adsorption mechanism of the dye onto the adsorbent. The maximum dye removal efficiency was obtained with the adsorbent amount of 500 mg (in 50 mL) and initial pH of 2 in 10 min for 20 mg/L ARS solution. Under these optimum conditions the complete removal of ARS was obtained while the maximum adsorption capacity was 38.51 mg/g. The well fitness of pseudo-second order kinetic model in the adsorption process was proved by kinetic studies. According to the obtained results, Freundlich isotherm model can suitably describe the adsorption of ARS on the sorbent. The achieved results from this study showed the excellent capability of CBNP for the adsorption of ARS

Laboratory Investigation of the Parameters of the Submerged Plates on the Turbidity Currents Characteristics

In dam reservoirs, the turbidity current is usually the cause of sediment transfer and deposition. Therefore, it is necessary to study this phenomenon. Here, experiments were made on the effects of the impermeable submerged plates on turbidity current head. In order to investigate the effects of the impermeable submerged plates, some parameters of the plates were changed, such as shape, angle of mounting of the plates with respect to the current axis, location and the dimensions of the plates. The results showed that the flow velocity of the turbidity current decreased by 25 to 27.1% with respect to the control state in case of different shapes of plates mounted. The analysis of the position of the plates showed that in different conditions, the flow velocity decreases 45.1% relative to the control state. Various mounting angles also resulted in 8.6 to 27.1% lower velocity relative to the control. Changing the width and height of the plates reduced the head velocity from 21.8 to 43.9% and 10 to 45.2%