Dependability Modeling and Assessment in UML-Based Software Development

Most approaches for adaptive systems rely on models, particularly behaviour or architecture models, which describe the system and the environment in which it operates. One of the difficulties in creating such models is uncertainty about the accuracy and completeness of the models. Engineers therefore make assumptions which may prove to be invalid at runtime. In this paper we introduce a rigorous, tiered framework for combining behaviour models, each with different associated assumptions and risks. These models are used to generate operational strategies, through techniques such controller synthesis, which are then executed concurrently at runtime. We show that our framework can be used to adapt the functional behaviour of the system: through graceful degradation when the assumptions of a higher level model are broken, and through progressive enhancement when those assumptions are satisfied or restored.

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“…[34]), model driven development (e.g [25,8,49,32]), planning (e.g. [42,10,44]) and supervisory control (e.g.…”

Section: Related Workmentioning

confidence: 99%

Hope for the best, prepare for the worst: multi-tier control for adaptive systems

D’Ippolito

Braberman

Kramer

et al. 2014

Proceedings of the 36th International Conference on Software Engineering

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“…Emerging automata theories [ 19 ], graph-based approaches [ 20 ], and formal methods [ 21 ] in software engineering supply many valuable solutions for describing and analyzing such complicated state changes and interactive behaviors in distributed systems, which provide us with constructive ideas. In particular, a finite state automaton (FSA) [ 22 ] has been widely used in the analysis and behavior modeling for various practical moderate-scale systems.…”

Section: Related Workmentioning

confidence: 99%

Dynamic and Quantitative Method of Analyzing Service Consistency Evolution Based on Extended Hierarchical Finite State Automata

Liu

Tang

Ling

et al. 2014

The Scientific World Journal

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This paper is concerned with the dynamic evolution analysis and quantitative measurement of primary factors that cause service inconsistency in service-oriented distributed simulation applications (SODSA). Traditional methods are mostly qualitative and empirical, and they do not consider the dynamic disturbances among factors in service's evolution behaviors such as producing, publishing, calling, and maintenance. Moreover, SODSA are rapidly evolving in terms of large-scale, reusable, compositional, pervasive, and flexible features, which presents difficulties in the usage of traditional analysis methods. To resolve these problems, a novel dynamic evolution model extended hierarchical service-finite state automata (EHS-FSA) is constructed based on finite state automata (FSA), which formally depict overall changing processes of service consistency states. And also the service consistency evolution algorithms (SCEAs) based on EHS-FSA are developed to quantitatively assess these impact factors. Experimental results show that the bad reusability (17.93% on average) is the biggest influential factor, the noncomposition of atomic services (13.12%) is the second biggest one, and the service version's confusion (1.2%) is the smallest one. Compared with previous qualitative analysis, SCEAs present good effectiveness and feasibility. This research can guide the engineers of service consistency technologies toward obtaining a higher level of consistency in SODSA.

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“…This feature is essential to model the rescheduling process of faulty map and reduce tasks. Finite State Machine (FSM) (Bernardi et al, 2012) and Petri Net (PN) (Callou et al, 2012) are the main approaches to model distributed systems involving their dependability properties. FSM abstracts the details of the system behavior and enables to a direct relation to the MapReduce processing steps.…”

Section: Iceis2013-15thinternationalconferenceonenterpriseinformationmentioning

confidence: 99%

“…We consider the representative fault cases for the dependability testing of MapReduce systems as generated through an abstraction of its fault tolerance mechanism. This approach is successfully used to test other systems (Echtle and Leu, 1994;Ambrosio et al, 2005;Bernardi et al, 2012). It guides the generation to a finite set of fault cases that should be tolerated, and that they must be tested to ensure the system dependability.…”

Section: Generating Representative Fault Casesmentioning

confidence: 99%

“…The fault case generation is commonly done randomly or by the Test Engineer (Benso et al, 2007;Chandra et al, 2007;Henry, 2009;Bernardi et al, 2012;Jacques-Silva et al, 2006;Lefever et al, 2004). These approaches are inadequate for the dependability testing of MapReduce systems because they disregard the internals of the fault tolerance mechanism, i.e., they ignore the behavior of fault recovery protocols regarding the different processing steps, e.g., they inject faults in some machines (fails 3 of 10) for some period (from 30 to 40 sec).…”

Section: Related Workmentioning

confidence: 99%

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Dependability Testing of MapReduce Systems

Marynowski¹,

Pimentel²,

Weber³

et al. 2013

Proceedings of the 15th International Conference on Enterprise Information Systems

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MapReduce systems have been widely used by several applications, from search engines to financial and commercial systems. There is considerable enthusiasm around MapReduce systems due to their simplicity and scalability. However, they lack a testing approach and framework ensuring their dependability. In this work, we propose a complete dependability testing solution for MapReduce systems. This solution is a model-based approach to generate representative fault cases, and a testing framework to automate their execution. Moreover, we introduce a new way to model distributed components using Petri Nets, and we show the promising results of the proposed testing framework, HadoopTest, on identifying faulty systems in real deployment scenarios.

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Dependability Modeling and Assessment in UML-Based Software Development

Cited by 7 publications

References 17 publications

Hope for the best, prepare for the worst: multi-tier control for adaptive systems

Hope for the best, prepare for the worst: multi-tier control for adaptive systems

Dynamic and Quantitative Method of Analyzing Service Consistency Evolution Based on Extended Hierarchical Finite State Automata

Dependability Testing of MapReduce Systems

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