In this paper, we show how to implement the conformance relation on transition systems. The computability of this relation relies on the composition of two operators: the reduction relation whose computability has been proven in our previous work, and the merge function of acceptance graphs associated with transition systems under comparison. It is formally demonstrated, and illustrated through a case study whose analysis is performed by a JAVA prototype we have developed. This research work is developed in order to be applied in a larger context: our goal is to support modelers to develop UML state machine through an incremental modelling method which is able to guarantee that model upgrading does not introduce inconsistencies. Hence, these works lead to a semantics for the specialisation relation between UML State Machines.
Modelling component behaviour is widely recognised as a complex task during the specification and design phases of reactive systems. Our proposal for treating this problem involves an incremental approach that allows UML state machines to be built using a composition of two types of development: model extension for adding services or behaviours, and refinement for adding details or eliminating non-determinism. At each step of the development process, the current model is verified for compliance with the model obtained during the previous step, in such a way that initial liveness properties are preserved. The novelty of this work lies in the possibility to combine and sequence both refinement and extension developments. This iterative process is usually not taken into account in conventional refinement relations. This set of development techniques and verification means are assembled into a framework called IDF (Incremental Development Framework), which is supported by a tool, under the acronym IDCM (Incremental Development of Compliant Models), developed herein in addition to the Topcased UML tool.
Due to the variety of sensors and portability of mobile phones, an increasing amount of mobile apps are released for the purpose of health monitoring. To design a new health monitoring app, a conventional approach is to define a goal model with the intervention of stakeholders. As there are a large number of apps in this domain, many of them have similar features, which can be exploited to reduce the time consumption of requirements elicitation, improve their quality and help the requirements prioritization. In this paper, we propose a novel requirements engineering approach by analysing similar apps. In this approach, we identify similar apps and analyze their descriptions, user reviews, Android APK and source code for the construction and enrichment of a Domain Feature Model. This model will be used as a support for the requirements engineers in different phases of requirements engineering.
ISBN: 0-8186-2985-1 website : http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?isnumber=5869&arnumber=224447&count=43&index=39As complexity of circuits has increased and design techniques have evolved, testing them has evolved as well. This evolution has led to take into account high-level behavioral descriptions of circuits for generating their test patterns. The authors explain the reasons which have motivated research laboratory to become interested in behavioral generation. Having surveyed the representative work of the domain, the authors present their approach for generating test patterns from high-level behavioral description
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