Property Checking Research Articles

A higher-order transformation approach to the formalization and analysis of BPMN using graph transformation systems

The Business Process Modeling Notation (BPMN) is a widely used standard notation for defining intra- and inter-organizational workflows. However, the informal description of the BPMN execution semantics leads to different interpretations of BPMN elements and difficulties in checking behavioral properties. In this article, we propose a formalization of the execution semantics of BPMN that, compared to existing approaches, covers more BPMN elements while also facilitating property checking. Our approach is based on a higher-order transformation from BPMN models to graph transformation systems. To show the capabilities of our approach, we implemented it as an open-source web-based tool.

Formal design, verification and implementation of robotic controller software via RoboChart and RoboTool

Current practice in simulation and implementation of robot controllers is usually undertaken with guidance from high-level design diagrams and pseudocode. Thus, no rigorous connection between the design and the development of a robot controller is established. This paper presents a framework for designing robotic controllers with support for automatic generation of executable code and automatic property checking. A state-machine based notation, RoboChart, and a tool (RoboTool) that implements the automatic generation of code and mathematical models from the designed controllers are presented. We demonstrate the application of RoboChart and its related tool through a case study of a robot performing an exploration task. The automatically generated code is platform independent and is used in both simulation and two different physical robotic platforms. Properties are formally checked against the mathematical models generated by RoboTool, and further validated in the actual simulations and physical experiments. The tool not only provides engineers with a way of designing robotic controllers formally but also paves the way for correct implementation of robotic systems.

Runtime verification on abstract finite state models

Finite-state models are ubiquitous in the study of concurrent systems, especially controllers and servers that operate in a repetitive cycle. In this paper, we show how to extract finite state models from a run of a multi-threaded Java program and carry out runtime verification of correctness properties. These properties include data-oriented and control-oriented properties; the former express correctness conditions over the data fields of objects, while the latter are concerned with the correct flow of control among the modules of larger software. As the extracted models can become very large for long runs, the focus of this paper is on constructing reduced models with user-defined abstraction functions that map a larger domain space to a smaller one. The abstraction functions should be chosen so that the resulting model is property preserving, i.e., proving a property on the abstract model carries over to the concrete model. The main contribution of this paper is in showing how runtime verification can be made efficient through online property checking on property-preserving abstract models. The property specification language resembles a propositional linear temporal logic augmented with simple datatypes and operators. Classic concurrency examples and larger case studies (Multi-rotor Drone Controller, OAuth Protocol) are presented in order to demonstrate the usefulness of our proposed techniques, which are incorporated in an Eclipse plug-in for runtime visualization and verification of Java programs.

Model Checking of Possibilistic Linear-Time Properties Based on Generalized Possibilistic Decision Processes

Model checking possibilistic linear-time properties was investigated by Li (2017). However, nondeterminism of the system is absent in previous studies. Therefore, in order to permit both possibilistic and nondeterministic choices, we use the generalized possibilistic decision process (GPDP) as a model of the system. First, the definition of GPDP describing the behavior of nondeterministic system is given in detail, the resolution of nondeterminism is performed by using the notion of schedulers, and the semantics of generalized possibilistic linear-temporal logic (GPoLTL) with schedulers are defined. Second, we study possibilistic model checking of some fuzzy linear-time properties under GPDP. Since there are many (infinite) schedulers satisfying a certain linear timing property in a given state of a GPDP, it is particularly critical to study the optimal strategy and its corresponding possible measure, which is called extremal possibility model checking. For some special fuzzy linear-time properties, such as constrained reachability, step-bounded constrained reachability, reachability, always reachability, repeated reachability, persistence reachability, we present complete solution to the optimal (including maximum and minimum cases) possibilistic model checking of the above reachability using the fixpoint techniques. We also introduce fuzzy !-regular properties in GPDP and show that their model checking can be simplified by repeated reachability. The algorithms for model checking are also provided. Additionally, an example is presented to illustrate the methods described in the paper.

Flexible temporal constraint management in modularized processes

Managing temporal process constraints in modularized processes is an important task, both during the design, as it allows the reuse of temporal (child) process models, and during the checking of temporal properties of processes, as it avoids the necessity of “unfolding” child processes within the main process model. Taking into account the capability of providing modular solutions, modeling and checking temporal features of processes is still an open problem in the context of process-aware information systems.In this paper, we present and discuss a novel approach to represent flexible temporal constraints in modularized time-aware BPMN process models.To support temporal flexibility, allowed task durations are represented through guarded ranges that allow a limited (guarded) restriction of task durations during process execution if it is necessary to guarantee the satisfaction of all temporal constraints. We, then, propose how to derive a compact representation of the overall temporal behavior of such time-aware BPMN models. Such compact representation of child processes allows us to check the dynamic controllability (DC) of a parent time-aware process model without “unfolding” the child process models. Dynamic controllability guarantees that process models can have process instances (i.e., executions) satisfying all the temporal constraints for any possible combination of allowed durations of tasks and child processes. Possible approaches for even more flexibility by solving some kinds of DC violations are then introduced.We use a real process model from a healthcare domain as a motivating example, and we also present a proof-of-concept prototype confirming the concrete applicability of the solutions we propose, followed by an experimental evaluation.

Union Models for Model Families: Efficient Reasoning over Space and Time

A model family is a set of related models in a given language, with commonalities and variabilities that result from evolution of models over time and/or variation over intended usage (the spatial dimension). As the family size increases, it becomes cumbersome to analyze models individually. One solution is to represent a family using one global model that supports analysis. In this paper, we propose the concept of union model as a complete and concise representation of all members of a model family. We use graph theory to formalize a model family as a set of attributed typed graphs in which all models are typed over the same metamodel. The union model is formalized as the union of all graph elements in the family. These graph elements are annotated with their corresponding model versions and configurations. This formalization is independent from the modeling language used. We also demonstrate how union models can be used to perform reasoning tasks on model families, e.g., trend analysis and property checking. Empirical results suggest potential time-saving benefits when using union models for analysis and reasoning over a set of models all at once as opposed to separately analyzing single models one at a time.

Natural Phytocompounds from Common Indian Spices for Identification of Three Potential Inhibitors of Breast Cancer: A Molecular Modelling Approach.

Breast cancer is the second most common cancer-related cause of death for women throughout the globe. In spite of some effective measures, the main concerns with traditional anti-cancer chemotherapy are its low bioavailability, physical side effects, acquired resistance of cancer cells and non-specific targeting. Now researchers have taken the initiative to establish natural product-based therapy methods and to identify viable hits for future lead optimization in the development of breast cancer medication. Our study aims to identify the potent phytocompounds from five very popular Indian spices (Zingiber officinale Roscoe, Cuminum cyminum L., Piper nigrum L., Curcuma longa L., and Allium sativum L.). From these spices, a total of 200 phytocompounds were identified and screened against three target genes, namely, cyclin-dependent kinase 8 (CDK 8), progesterone receptor (PR) and epidermal growth factor receptor (EGFR), through structure-based virtual screening using iGEMDOCK 2.1 software. Based on the binding affinity score, the top three phytocompounds against each target protein (cynaroside (−149.66 Kcal/mol), apigetrin (−139.527 Kcal/mol) and curcumin (−138.149 Kcal/mol) against CDK8; apigetrin (−123.298 Kcal/mol), cynaroside (−118.635 Kcal/mol) and xyloglucan (−113.788 Kcal/mol) against PR; cynaroside (−119.18 Kcal/mol), apigetrin (−105.185 Kcal/mol) and xyloglucan (−105.106 Kcal/mol) against EGFR) were selected. Apigetrin, cynaroside, curcumin, and xyloglucan were finally identified for further docking analysis with the respective three target proteins. Autodock 4.2 was applied to screen the optimal binding position and to assess the relative intensity of binding interactions. In addition, the ADME/T property checks and bioactivity scores analysis of were performed to understand the suitability of these four phytocompounds to be potential candidates for developing effective and non-toxic anticancer agents. Based on this in silico analysis, we believe this study could contribute to current efforts to develop new drugs for treating breast cancer.

REST APIs Cloud Service Security Checks

Abstract: REST APIs are used by the majority of modern cloud and web services. This paper explains how an attacker can take advantage of REST API flaws to gain access to a service. We introduce four new security rules that take advantage of REST API’s and then demonstrate how a stateful REST API fuzzer can be extended with active property checkers that automatically test and identify violations of these rules. Then we talk about how to implement such checkers in both ways modularly and efficiently. Using these tools, we discovered new bugs in a number of production Azure and Office365 cloud services and discussed their security implications and resolve all these issues

Hardware Trojan Detection Using Effective Property-Checking Method

Hardware Trojans refer to additional logic maliciously implanted by attackers in integrated circuits (ICs). Because of the potential security threat of hardware Trojans, they have attracted extensive attention to security issues. As a formal verification method, property checking has been proved to be a powerful solution for hardware Trojan detection. However, existing property-checking methods are limited by the unity of security properties and the model explosion problem of formal models. The limitations above hinder the practical applications of these methods. To alleviate these challenges, we propose an effective property-checking method for hardware Trojan detection. Specifically, we establish the formal model based on the principle of finite state machine (FSM), and the method can alleviate the model explosion problem. For property writing, we extract the core behavior characteristics of hardware Trojans and then generate properties for the verification of certain types of hardware Trojans. Experimental results demonstrate that our approach is applicable to detect information leakage and denial of service (DoS) hardware Trojans by verifying security properties.

Verification of Distributed Systems via Sequential Emulation

Sequential emulation is a semantics-based technique to automatically reduce property checking of distributed systems to the analysis of sequential programs. An automated procedure takes as input a formal specification of a distributed system, a property of interest, and the structural operational semantics of the specification language and generates a sequential program whose execution traces emulate the possible evolutions of the considered system. The problem as to whether the property of interest holds for the system can then be expressed either as a reachability or as a termination query on the program. This allows to immediately adapt mature verification techniques developed for general-purpose languages to domain-specific languages, and to effortlessly integrate new techniques as soon as they become available. We test our approach on a selection of concurrent systems originated from different contexts from population protocols to models of flocking behaviour. By combining a comprehensive range of program verification techniques, from traditional symbolic execution to modern inductive-based methods such as property-directed reachability, we are able to draw consistent and correct verification verdicts for the considered systems.

Analyzing stochastic reward nets by model checking and parallel simulation

This paper deals with Stochastic Reward Nets (SRN), which are a powerful extension of Generalized Stochastic Petri Nets (GSPN). SRN have proved their usefulness in modelling and analysis of performance, availability and reliability of complex timed systems. SRN are supported by special-case tools like the Stochastic Petri Net Package (SPNP) which enables both analytic (based on Markov Reward Models) and simulative studies. The work described in this paper argues that there is still a gap in SRN analysis concerning functional correctness and non-deterministic property checking. Toward this a novel approach is proposed, which is based on two developed tools. First a formal reduction of SRN onto the Timed Automata (TA) of the popular Uppaal toolbox was defined and implemented. The Uppaal reduction enables a more complete investigation of SRN models, not allowed by existing SRN tools. However, the practical use of Uppaal forbids to study the performance of large models. Then, an SRN kernel, inspired by the carried formal Uppaal modelling and reasoning, was achieved in Java using the Theatre actor system. The realization supports the parallel simulation of scalable models. The paper applies the developed tools to a realistic grid-computing model and reports some experimental results, together with good execution performance (speedup) when using a scalable version of the grid model on a shared memory multi-core machine.

In silico Screening of Natural Phytocompounds Towards Identification of Potential Lead Compounds to Treat COVID-19.

COVID-19 is one of the members of the coronavirus family that can easily assail humans. As of now, 10 million people are infected and above two million people have died from COVID-19 globally. Over the past year, several researchers have made essential advances in discovering potential drugs. Up to now, no efficient drugs are available on the market. The present study aims to identify the potent phytocompounds from different medicinal plants (Zingiber officinale, Cuminum cyminum, Piper nigrum, Curcuma longa, and Allium sativum). In total, 227 phytocompounds were identified and screened against the proteins S-ACE2 and Mpro through structure-based virtual screening approaches. Based on the binding affinity score, 30 active phytocompounds were selected. Amongst, the binding affinity for beta-sitosterol and beta-elemene against S-ACE2 showed −12.0 and −10.9 kcal/mol, respectively. Meanwhile, the binding affinity for beta-sitosterol and beta-chlorogenin against Mpro was found to be −9.7 and −8.4 kcal/mol, respectively. Further, the selected compounds proceeded with molecular dynamics simulation, prime MM-GBSA analysis, and ADME/T property checks to understand the stability, interaction, conformational changes, binding free energy, and pharmaceutical relevant parameters. Moreover, the hotspot residues such as Lys31 and Lys353 for S-ACE2 and catalytic dyad His41 and Cys145 for Mpro were actively involved in the inhibition of viral entry. From the in silico analyses, we anticipate that this work could be valuable to ongoing novel drug discovery with potential treatment for COVID-19.

Property Checking with Interpretable Error Characterization for Recurrent Neural Networks

This paper presents a novel on-the-fly, black-box, property-checking through learning approach as a means for verifying requirements of recurrent neural networks (RNN) in the context of sequence classification. Our technique steps on a tool for learning probably approximately correct (PAC) deterministic finite automata (DFA). The sequence classifier inside the black-box consists of a Boolean combination of several components, including the RNN under analysis together with requirements to be checked, possibly modeled as RNN themselves. On one hand, if the output of the algorithm is an empty DFA, there is a proven upper bound (as a function of the algorithm parameters) on the probability of the language of the black-box to be nonempty. This implies the property probably holds on the RNN with probabilistic guarantees. On the other, if the DFA is nonempty, it is certain that the language of the black-box is nonempty. This entails the RNN does not satisfy the requirement for sure. In this case, the output automaton serves as an explicit and interpretable characterization of the error. Our approach does not rely on a specific property specification formalism and is capable of handling nonregular languages as well. Besides, it neither explicitly builds individual representations of any of the components of the black-box nor resorts to any external decision procedure for verification. This paper also improves previous theoretical results regarding the probabilistic guarantees of the underlying learning algorithm.

Recycling the material waste bound in construction sites using bitumen approach

This research paper proposes the Bitublock is a new development unit that is made altogether out of reused and waste aggregates bound in a lattice of bitumen. The creation isn't yet the whole business creation yet broad testing and checking of properties are exhibited superb potential for replacing the cement and clay based structure block items. One of the key highlights pertinent to future achievement lies in the capacity to choose the input formula fixings and cyclic conditions to coordinate by large exceeded current determinations for a scope of goods or end clients. This adaptability gives a reasonable case to be seen as a new goods but only a alternate for existing development units. Bitublock mixes with bituminous bound waste materials such as plastics, concrete waste, construction waste, coal fly ash, bagasse bottom ash and quarry dust. The block samples where 220 mm × 100 mm × 50 mm in size and compacted. The curing regime 200 °C for 24 h gives acceptable compressive strength that is equivalent with standard coarse aggregate concrete blocks. The optimum bitumen content of these blocks was found to be 6.5% the samples were tested after 14 days.

Reachability of Patterned Conditional Pushdown Systems

Conditional pushdown systems (CPDSs) extend pushdown systems by associating each transition rule with a regular language over the stack alphabet. The goal is to model program verification problems that need to examine the runtime call stack of programs. Examples include security property checking of programs with stack inspection, compatibility checking of HTML5 parser specifications, etc. Esparza et al. proved that the reachability problem of CPDSs is EXPTIME-complete, which prevents the existence of an algorithm tractable for all instances in general. Driven by the practical applications of CPDSs, we study the reachability of patterned CPDS (pCPDS) that is a practically important subclass of CPDS, in which each transition rule carries a regular expression obeying certain patterns. First, we present new saturation algorithms for solving state and configuration reachability of pCPDSs. The algorithms exhibit the exponential-time complexity in the size of atomic patterns in the worst case. Next, we show that the reachability of pCPDSs carrying simple patterns is solvable in fixed-parameter polynomial time and space. This answers the question on whether there exist tractable reachability analysis algorithms of CPDSs tailored for those practical instances that admit efficient solutions such as stack inspection without exception handling. We have evaluated the proposed approach, and our experiments show that the pattern-driven algorithm steadily scales on pCPDSs with simple patterns.

Proactive policing in the United States: a national survey

PurposeTo measure the practice and management of proactive policing in local American police agencies and assess them in comparison to recommendations of the National Academies of Sciences (NAS) Committee on Proactive Policing.Design/methodology/approachA survey was conducted with a national sample of American police agencies having 100 or more sworn officers to obtain detailed information about the types of proactive work that officers engage in, to quantify their proactive work and to understand how the agencies measure and manage those activities. Responding agencies (n = 180) were geographically diverse and served populations of approximately half a million persons on average.FindingsProactivity as practiced is much more limited in scope than what the NAS envisions. Most agencies track only a few forms of proactivity and cannot readily estimate how much uncommitted time officers have available for proactive work. Measured proactivity is mostly limited to traffic stops, business and property checks and some form of directed or general preventive patrol. Many agencies have no formal policy in place to define or guide proactive activities, nor do they evaluate officer performance on proactivity with a detailed and deliberate rubric.Originality/valueThis is the first national survey that attempts to quantify proactive policing as practiced broadly in the United States. It provides context to the NAS recommendations and provides knowledge about the gap between practice and those recommendations.

Property Satisfiability Analysis for Product Lines of Modelling Languages

Software engineering uses models throughout most phases of the development process. Models are defined using modelling languages. To make these languages applicable to a wider set of scenarios and customizable to specific needs, researchers have proposed using product lines to specify modelling language variants. However, there is currently a lack of efficient techniques for ensuring correctness with respect to properties of the models accepted by a set of language variants. This may prevent detecting problematic combinations of language variants that produce undesired effects at the model level. To attack this problem, we first present a classification of instantiability properties for language product lines. Then, we propose a novel approach to lifting the satisfiability checking of model properties of individual language variants, to the product line level. Finally, we report on an implementation of our proposal in the <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Merlin</small> tool, and demonstrate the efficiency gains of our lifted analysis method compared to an enumerative analysis of each individual language variant.

Implementing a semi-causal domain-specific language for context detection over binary sensors

In spite of the fact that many sensors in use today are binary (i.e. produce only values of 0 and 1), and that useful context-aware applications are built exclusively on top of them, there is currently no development approach specifically targeted to binary sensors. Dealing with notions of state and state combinators, central to binary sensors, is tedious and error-prone in current approaches. For instance, developing such applications in a general programming language requires writing code to process events, maintain state and perform state transitions on events, manage timers and/or event histories. In another paper, we introduced a domain specific language (DSL) called Allen, specifically targeted to binary sensors. Allen natively expresses states and state combinations, and detects contexts on line, on incoming streams of binary events. Expressing state combinations in Allen is natural and intuitive due to a key ingredient: semi-causal operators. That paper focused on the concept of the language and its main operators, but did not address its implementation challenges. Indeed, online evaluation of expressions containing semi-causal operators is difficult, because semi-causal sub-expressions may block waiting for future events, thus generating unknown values, besides 0 and 1. These unknown values may or may not propagate to the containing expressions, depending on the current value of the other arguments. This paper presents a compiler and runtime for the Allen language, and shows how they implement its state combining operators, based on reducing complex expressions to a core subset of operators, which are implemented natively. We define several assisted living applications both in Allen and in a general scripting language. We show that the former are much more concise in Allen, achieve more effective code reuse, and ease the checking of some domain properties.

Model Checking of Real-Time Properties for Embedded Assembly Program Using Real-Time Temporal Logic RTCTL and Its Application to Real Microcontroller Software

Model Checking of Real-Time Properties for Embedded Assembly Program Using Real-Time Temporal Logic RTCTL and Its Application to Real Microcontroller Software

Model checking of robustness properties in trust and reputation systems

Trust and reputation systems (TRSs) are used in cooperative environments where an agent needs to make a decision for requesting or performing a service. However, TRSs can be abused by malicious agents who do sequences of dishonest actions (attacks). Although there are proposals on verification of TRSs against attacks, they are not comprehensive enough to evaluate various Trust Computation Models (TCMs) and/or do not provide sufficient expressive power to specify different required robustness properties. In this paper, we introduce a comprehensive framework for specifying and verifying various robustness properties in TRSs through model checking approach. The proposed framework includes three main parts: (1) a logic for specification of robustness properties of TRSs named Probabilistic Action and Reward based Computation Tree Logic (PARCTL), (2) an enhanced version of our previously proposed model for specifying TRSs in hostile environments named Trust and Reputation Interaction Model (TRIM), and (3) the required algorithms for quantitative and probabilistic model checking of PARCTL properties over the specified model. The proposed framework has been implemented as a tool named TRIM-Checker. Our experimental results on robustness analysis of famous eBay, Beta, and CORE TCMs using TRIM-Checker are presented and their robustness against attacks is evaluated and compared together.