Computation Tree Logic Model Checking Research Articles

Business Process Modeled with BPMN and CTL Model Checking

Despite the richness of the BPMN language and its advantages for the specification of business processes, it remains a semi-formal language that does not allow rigorous verification of the specifications produced with it, and does not offer any methodological support to cover the verification phase. Therefore, several works have been proposed with the aim of describing the semantics of the BPMN language by a mathematical formalism. In this paper we address the issue of verifying BPMN models with an approach based on model-checking, where we focus on soundness, fairness, and safety properties. Thus by having a business process modeled by BPMN, a formal semantics for BPMN models based on Kripke structure will be provided for a formal verification of correctness. The properties are expressed with CTL (Computation Tree Logic) formulas. At the end, the model checker NuSMV is used for the verification of the formula.

Possibilistic Cost Computation Tree Logic and Related Equivalence, Abstraction Technique

Recently, probabilistic Kripke structures have been used to represent uncertain systems; nevertheless, important transition costs were ignored in earlier studies, making it impossible to model some uncertain systems with costs. To compensate for the major shortcoming, this research addresses the transition costs suggested in uncertain systems. First of all, we offer possibilistic Kripke cost structures and associated possibilistic costs such as cumulative cost and possibilistic expected cost. As the verification model, furthermore, we investigated the syntax and semantics of possibilistic cost computation tree logic and utilized them to develop verification characteristics of possibilistic Kripke cost structures. Finally, as solutions to the state space explosion problem of possibilistic cost computation tree logic model checking, abstraction and equivalence are presented as methods to reduce the state numbers and frameworks of possibilistic Kripke cost structures.

Computation Tree Logic Formula Model Checking Using DNA Computing

Computation tree logic model checking is a formal verification technology that can ensure the correctness of systems. The vast storage density of deoxyribonucleic acid (DNA) molecules and the massive parallelism of DNA computing offer new methods for computation tree logic model checking. In this study, we propose a computation tree logic model checking method based on DNA computing. First, a system to-be-checked and a computation tree logic formula are encoded by single-stranded DNA molecules. Second, these singlestranded DNA molecules are mixed to spontaneously hybridize and form partial or complete double-stranded molecules. Finally, a series of molecular manipulations are applied to detect the double-stranded molecules so that the result whether the system satisfies the computation tree logic formula is obtained. Biological simulations confirm the validity of the new method.

Computation tree logic model checking based on multi-valued possibility measures

Multi-valued model checking has been studied extensively recently, but important uncertain information contained in systems of multi-valued logics has not been considered in previous work and, as a consequence, some serious deficiencies arise. To make up for these deficiencies, this paper considers the possibility information implied in multi-valued systems. Precisely, we investigate computation tree logic model checking based on multi-valued possibility measures. We model multi-valued logic systems by multi-valued Kripke structures (MvKSs) and specify their verification properties by multi-valued computation tree logic (MvCTL) formulae. Based on generalized possibility measures and generalized necessity measures, an MvCTL model checking method is proposed, the pseudocode of the corresponding model checking algorithm is presented, and its time complexity is analyzed in detail. Furthermore, after detailed comparisons with χCTL (introduced in Chechik et al. [10]) and the classical CTL, we show that MvCTL is more general than χCTL, but cannot be reduced to the classical CTL. The conditions on lattice and MvKS under which MvCTL is equivalent to χCTL are given. Finally, some examples and a case study are given to illustrate the MvCTL model-checking method.

Methodology for Integrating Computational Tree Logic Model Checking in Unified Modelling Language Artefacts A Case Study of an Embedded Controller


 
 
 A unified modelling language (UML) based formal verification methodology that can be easily integrated into an embedded system software development life cycle is suggested. The approach augments UML diagrams with formal models through an interfacing domain and adds semantics to these diagrams. The suggested methodology; commences from functional specification and use case modelling, selects the most critical behaviour where formal verification can add value to the development cycle, analyses the selected behaviour using UML state transition diagram, derives a state chart matrix from the same, and a high level language software translates the state chart matrix to a labelled transition system. Safety properties are derived from system specifications and are expressed as computation tree logic (CTL) formulae. CTL model-checking algorithm from the literature is used for model- checking. The applicability of the suggested approach is established using a safety critical embedded controller used for deployment and recovery of sensor structures from an airborne platform.
 
 

Performing CTL model checking via DNA computing

The computation using deoxyribonucleic acid (DNA) molecules provides an enormous parallel method that breaks through the limitations of the efficiency of traditional electronic computers. Model checking is a standard formal verification technique, which has been widely used in many fields of computation. It is also a well-known complex problem in computing theory. Until now, there is only one basic formula in the computation tree logic (CTL), for which model checking via DNA computing can be conducted. To this end, Adleman’s model based on DNA computing is used in this paper, based on which a series of DNA-computing-based model-checking algorithms to check the four basic CTL formulas are proposed. As a result, a core of the DNA version of the CTL model-checking problem is solved. The simulated experimental results show that the new algorithms are valid and can be properly implemented in molecular biology.

Quantitative Computation Tree Logic Model Checking Based on Generalized Possibility Measures

We study generalized possibilistic computation tree logic (GPoCTL) model checking in this paper, which is an extension of possibilistic computation logic model checking introduced by Li et al. (2014). The system is modeled by generalized possibilistic Kripke structures, and the verifying property is specified by a GPoCTL formula. Based on generalized possibility measures and generalized necessity measures, the method of GPoCTL model checking is discussed, and the corresponding algorithm and its complexity are shown in detail. Furthermore, the comparison between possibilistic computation tree logic and GPoCTL is given. Finally, a thermostat example is given to illustrate the GPoCTL model-checking method.

Computation tree logic model checking based on possibility measures

In order to deal with the systematic verification with uncertain information in possibility theory, Li and Li (2013) introduced model checking of linear-time properties in which the uncertainty is modeled by possibility measures. Xue, Lei and Li (2011) defined computation tree logic (CTL) based on possibility measures, which is called possibilistic CTL (PoCTL). This paper is a continuation of the above work. First, we study the expressiveness of PoCTL. Unlike probabilistic CTL, it is shown that PoCTL (in particular, qualitative PoCTL) is more powerful than CTL with respect to their expressiveness. The equivalent expressions of basic CTL formulae using qualitative PoCTL formulae are presented in detail. Some PoCTL formulae that cannot be expressed by any CTL formulae are presented. In particular, some qualitative properties of repeated reachability and persistence are expressed using PoCTL formulae. Next, adapting CTL model-checking algorithm, a method to solve the PoCTL model-checking problem and its time complexity are discussed in detail. Finally, an example is given to illustrate the PoCTL model-checking method.

Symbolic computation tree logic model checking of time Petri nets

Model checking is a technique to decide whether a system modeled by a state graph satisfies a temporal logic formula. A serious problem in model checking of practical systems is that the size of the state graphs becomes huge. One solution of this problem is symbolic model checking, in which sets of states and transition relations over states are represented and handled symbolically. This research studies symbolic model checking in which realtime systems are modeled by time Petri nets and specifications are expressed by computation tree logic formulas. As realtime systems potentially have infinite state spaces, techniques to reduce infinite state spaces to finite ones are necessary. This paper discusses a technique based on equivalence classes, called regions, of states as well as a technique to restrict the behavior of time Petri nets so that transitions fire only at integer times. The algorithm in the former approach is presented in detail and then some experimental results are shown. © 1997 Scripta Technica, Inc. Electron Comm Jpn Pt 3, 80(4): 11–20, 1997