A classification and comparison of model checking software architecture techniques

Zhang, Pengcheng; Muccini, Henry; Li, Bixin

doi:10.1016/j.jss.2009.11.709

Cited by 52 publications

(40 citation statements)

References 73 publications

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“…Most architectural properties to be verified by using model checking techniques are temporal [20], i.e., they are qualified and can be reasoned upon a sequence of system states along the time. In the literature, linear temporal logic (LTL) [18] has been often used as underlying formalism for specifying temporal architectural properties and verifying them through model checking.…”

Section: A Novel Notation For Expressing Properties In Dynamic Softwamentioning

confidence: 99%

“…Additionally, automated verification provides an efficient method to check the correctness of architectural design. As reported by Zhang et al [20], one of the most popular formal methods for analyzing software architectures is model checking, an exhaustive, automatic verification technique whose general goal is to verify if an architectural specification satisfies architectural properties [8]. It takes as inputs a representation of the system (e.g., an architecture description) and a set of property specifications expressed in some notation.…”

Section: Introductionmentioning

confidence: 99%

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Statistical Model Checking of Dynamic Software Architectures

Cavalcante

Quilbeuf

Traonouez

et al. 2016

Software Architecture

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Abstract. The critical nature of many complex software-intensive systems calls for formal, rigorous architecture descriptions as means of supporting automated verification and enforcement of architectural properties and constraints. Model checking has been one of the most used techniques to automatically analyze software architectures with respect to the satisfaction of architectural properties. However, such a technique leads to an exhaustive exploration of all possible states of the system under verification, a problem that becomes more severe when verifying dynamic software systems due to their typical non-deterministic runtime behavior and unpredictable operation conditions. To tackle these issues, we propose using statistical model checking (SMC) to support the analysis of dynamic software architectures while aiming at reducing effort, computational resources, and time required for this task. In this paper, we introduce a novel notation to formally express architectural properties as well as an SMC-based toolchain for verifying dynamic software architectures described in π-ADL, a formal architecture description language. We use a flood monitoring system to show how to express relevant properties to be verified, as well as we report the results of some computational experiments performed to assess the efficiency of our approach.

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Section: A Novel Notation For Expressing Properties In Dynamic Softwamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Statistical Model Checking of Dynamic Software Architectures

Cavalcante

Quilbeuf

Traonouez

et al. 2016

Software Architecture

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“…Zhang et al [30] report that linear temporal logic (LTL) [24] has been often used in the literature as underlying formalism for specifying temporal architectural properties and verifying them through model checking. LTL extends classical Boolean logic with temporal operators (a.k.a.…”

Section: Expressing Properties About Dynamic Systemsmentioning

confidence: 99%

“…Nonetheless, the state space might still be quite large and hence the use of such techniques may be a prohibitive choice in terms of execution time and computational resources. This is the case of model checking [8], a formal verification technique that is among the most frequently used ones in the analysis of software architectures [30].…”

Section: Introductionmentioning

confidence: 99%

A Logic for the Statistical Model Checking of Dynamic Software Architectures

Quilbeuf

Cavalcante

Traonouez

et al. 2016

Leveraging Applications of Formal Methods, Verification and Validation: Foundational Techniques

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Abstract. Dynamic software architectures emerge when addressing important features of contemporary systems, which often operate in dynamic environments subjected to change. Such systems are designed to be reconfigured over time while maintaining important properties, e.g., availability, correctness, etc. Verifying that reconfiguration operations make the system to meet the desired properties remains a major challenge. First, the verification process itself becomes often difficult when using exhaustive formal methods (such as model checking) due to the potentially infinite state space. Second, it is necessary to express the properties to be verified using some notation able to cope with the dynamic nature of these systems. Aiming at tackling these issues, we introduce DynBLTL, a new logic tailored to express both structural and behavioral properties in dynamic software architectures. Furthermore, we propose using statistical model checking (SMC) to support an efficient analysis of these properties by evaluating the probability of meeting them through a number of simulations. In this paper, we describe the main features of DynBLTL and how it was implemented as a plug-in for PLASMA, a statistical model checker.

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“…Formalizing software architectures, components, agents and services has generated a lot of interest during the last years (Zhang et al, 2010). Many approaches utilize process algebras as the foundational formalism (Bergstra et al, 2001).…”

mentioning

confidence: 99%

FSP and FLTL framework for specification and verification of middle-agents

Bădică¹,

Bǎdicǎ²

2011

International Journal of Applied Mathematics and Computer Science

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Agents are a useful abstraction frequently employed as a basic building block in modeling service, information and resource sharing in global environments. The connecting of requester with provider agents requires the use of specialized agents known as middle-agents. In this paper, we propose a formal framework intended to precisely characterize types of middle-agents with a special focus on matchmakers, brokers and front-agents by formally modeling their interactions with requesters and providers. Our approach is based on capturing interaction protocols between requesters, providers and middle-agents as finite state processes represented using FSP process algebra. The resulting specifications are formally verifiable using FLTL temporal logic. The main results of this work include (i) precise specification of interaction protocols depending on the type of middle-agent (this can also be a basis for characterizing types of middle-agents), (ii) improvement of communication between designers and developers and facilitation of formal verification of agent systems, (iii) guided design and implementation of agent-based software systems that incorporate middle-agents.

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A classification and comparison of model checking software architecture techniques

Cited by 52 publications

References 73 publications

Statistical Model Checking of Dynamic Software Architectures

Statistical Model Checking of Dynamic Software Architectures

A Logic for the Statistical Model Checking of Dynamic Software Architectures

FSP and FLTL framework for specification and verification of middle-agents

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