188,719 research outputs found

    Metamodel Instance Generation: A systematic literature review

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    Modelling and thus metamodelling have become increasingly important in Software Engineering through the use of Model Driven Engineering. In this paper we present a systematic literature review of instance generation techniques for metamodels, i.e. the process of automatically generating models from a given metamodel. We start by presenting a set of research questions that our review is intended to answer. We then identify the main topics that are related to metamodel instance generation techniques, and use these to initiate our literature search. This search resulted in the identification of 34 key papers in the area, and each of these is reviewed here and discussed in detail. The outcome is that we are able to identify a knowledge gap in this field, and we offer suggestions as to some potential directions for future research.Comment: 25 page

    A Model-Driven approach for functional test case generation

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    Test phase is one of the most critical phases in software engineering life cycle to assure the final system quality. In this context, functional system test cases verify that the system under test fulfills its functional specification. Thus, these test cases are frequently designed from the different scenarios and alternatives depicted in functional requirements. The objective of this paper is to introduce a systematic process based on the Model-Driven paradigm to automate the generation of functional test cases from functional requirements. For this aim, a set of metamodels and transformations and also a specific language domain to use them is presented. The paper finishes stating learned lessons from the trenches as well as relevant future work and conclusions that draw new research lines in the test cases generation context.Ministerio de Economía y Competitividad TIN2013-46928-C3-3-

    Improving NDT with Automatic Test Case Generation

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    The model-driven development defi nes the software development process as a set of iterations to create models and a set of transformations to obtain new models. From this point of view, this paper presents the enhancement of a model- driven approach, called navigational development techniques (NDT), by means of new models and transformations in order to generate test cases. It also states some conclusions from the research work and practical cases in which this approach was used.Ministerio de Ciencia e Innovación TIN2010-20057-C03-02Ministerio de Ciencia e Innovación TIN 2010-12312-

    Automating property-based testing of evolving web services

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    Web services are the most widely used service technology that drives the Service-Oriented Computing~(SOC) paradigm. As a result, effective testing of web services is getting increasingly important. In this paper, we present a framework and toolset for testing web services and for evolving test code in sync with the evolution of web services. Our approach to testing web services is based on the Erlang programming language and QuviQ QuickCheck, a property-based testing tool written in Erlang, and our support for test code evolution is added to Wrangler, the Erlang refactoring tool. The key components of our system include the automatic generation of initial test code, the inference of web service interface changes between versions, the provision of a number of domain specific refactorings and the automatic generation of refactoring scripts for evolving the test code. Our framework provides users with a powerful and expressive web service testing framework, while minimising users' effort in creating, maintaining and evolving the test model. The framework presented in this paper can be used by both web service providers and consumers, and can be used to test web services written in whatever language; the approach advocated here could also be adopted in other property-based testing frameworks and refactoring tools

    Didactic Networks: A proposal for e-learning content generation

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    The Didactic Networks proposed in this paper are based on previous publications in the field of the RSR (Rhetorical-Semantic Relations). The RSR is a set of primitive relations used for building a specific kind of semantic networks for artificial intelligence applications on the web: the RSN (Rhetorical-Semantic Networks). We bring into focus the RSR application in the field of elearning, by defining Didactic Networks as a new set of semantic patterns oriented to the development of eleaming applications. The different lines we offer in our research Jail mainly into three levels: • The most basic one is in the field of computational linguistics and related to Logical Operations on RSR (RSR Inverses and plurals. RSR combinations, etc), once they have been created. The application of Walter Bosma 's results regarding rhetorical distance application and treatment as semantic weighted networks is one of the important issues here. • In parallel, we have been working on the creation of a knowledge representation and storage model and data architecture capable of supporting the definition of knowledge networks based on RSR. • The third strategic line is in the meso-level, the formulation of a molecular structure of knowledge based on the most frequently used patterns. The main contribution at this level is the set of Fundamental Cognitive Networks (FCN) as an application of Novak's mental maps proposal. This paper is part of this third intermediate level, and the Fundamental Didactic Networks (FDN) are the result of the application of rhetorical theoiy procedures to the instructional theory. We have formulated a general set of RSR capable of building discourse, making it possible to express any concept, procedure or principle in terms of knowledge nodes and RSRs. The instructional knowledge can then be elaborated in the same way. This network structure expressing the instructional knowledge in terms of RSR makes the objective of developing web-learning lessons semi-automutkally possible, as well as any other type of utilities oriented towards the exploitation of semantic structure, such as the automatic question answering systems

    Automatic Generation of CHR Constraint Solvers

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    In this paper, we present a framework for automatic generation of CHR solvers given the logical specification of the constraints. This approach takes advantage of the power of tabled resolution for constraint logic programming, in order to check the validity of the rules. Compared to previous works where different methods for automatic generation of constraint solvers have been proposed, our approach enables the generation of more expressive rules (even recursive and splitting rules) that can be used directly as CHR solvers.Comment: to be published in Theory and Practice of Logic Programming, 16 pages, 2 figure

    Syntactic Abstraction of B Models to Generate Tests

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    In a model-based testing approach as well as for the verification of properties, B models provide an interesting solution. However, for industrial applications, the size of their state space often makes them hard to handle. To reduce the amount of states, an abstraction function can be used, often combining state variable elimination and domain abstractions of the remaining variables. This paper complements previous results, based on domain abstraction for test generation, by adding a preliminary syntactic abstraction phase, based on variable elimination. We define a syntactic transformation that suppresses some variables from a B event model, in addition to a method that chooses relevant variables according to a test purpose. We propose two methods to compute an abstraction A of an initial model M. The first one computes A as a simulation of M, and the second one computes A as a bisimulation of M. The abstraction process produces a finite state system. We apply this abstraction computation to a Model Based Testing process.Comment: Tests and Proofs 2010, Malaga : Spain (2010
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