Towards Systematic Mutations for and with ATL Model Transformations

Model transformation is a key technique to automate software engineering tasks, such as generating implementations of software systems from higher-level models. To enable this automation, transformation engines are used to synthesize various types of software artifacts from models, where the rules according to which these artifacts are generated are implemented by means of dedicated model transformation languages. Hence, the quality of the generated software artifacts depends on the quality of the transformation rules applied to generate them. Thus, there is the need for approaches to certify their behavior for a selected set of test models. As mutation analysis has proven useful as a practical testing approach, we propose a set of mutation operators for the ATLAS Transformation Language (ATL) derived by a comprehensive language-centric synthesis approach. We describe the rationale behind each of the mutation operators and propose an automated process to generate mutants for ATL transformations based on a combination of generic mutation operators and higher-order transformations. Finally, we describe a cost-effective solution for executing the obtained mutants.European Commission ICT Policy Support Programme 317859Ministerio de Ciencia e Innovación TIN2011-2379

UML-based Cloud Application Modeling with Libraries, Profiles, and Templates

Recently, several cloud modeling approaches have emerged. They address the diversity of cloud environments by introducing a considerable set of modeling concepts in terms of novel domain-specific languages. At the same time, general-purpose languages, such as UML, provide modeling concepts to represent software, platform and infrastructure artifacts from different viewpoints where the deployment view is of particular relevance for specifying the distribution of application components on the targeted cloud environments. However, the generic nature of UML’s deployment language calls for a cloud-specific extension to capture the plethora of cloud provider offerings at the modeling level. In this paper, we propose the Cloud Application Modeling Language (CAML) to facilitate expressing cloud-based deployments directly in UML, which is especially beneficial for migration scenarios where reverse-engineered UML models are tailored towards a selected cloud environment. We discuss CAML’s realization as a UML internal language that is based on a model library for expressing deployment topologies and a set of profiles for wiring them with cloud provider offerings. Finally, we report on the use of UML templates to contribute application deployments as reusable blueprints and identify conceptual mappings between CAML and the recently standardized TOSCA.European Commission ICT Policy Support Programme 31785

XMLText: From XML Schema to Xtext

A multitude of Domain-Specific Languages (DSLs) have been implemented with XML Schemas. While such DSLs are well adopted and flexible, they miss modern DSL editor functionality. Moreover, since XML is primarily designed as a machine-processible format, artifacts defined with XMLbased DSLs lack comprehensibility and, therefore, maintainability. In order to tackle these shortcomings, we propose a bridge between the XML Schema Definition (XSD) language and text-based metamodeling languages. This bridge exploits existing seams between the technical spaces XMLware, modelware, and grammarware as well as closes identified gaps. The resulting approach is able to generate Xtextbased editors from XSDs providing powerful editor functionality, customization options for the textual concrete syntax style, and round-trip transformations enabling the exchange of data between the involved technical spaces. We evaluate our approach by a case study on TOSCA, which is an XML-based standard for defining Cloud deployments. The results show that our approach enables bridging XMLware with modelware and grammarware in several ways going beyond existing approaches and allows the automated generation of editors that are at least equivalent to editors manually built for XML-based languages.European Commission ICT Policy Support Programme 31785

fREX: fUML-based Reverse Engineering of Executable Behavior for Software Dynamic Analysis

International audienceReverse engineering is still a challenging process, notably because of the growing number, heterogeneity, complexity, and size of software applications. While the analysis of their structural elements has been intensively investigated, there is much less work covering the reverse engineering of their behavioral aspects. To further stimulate research on this topic, we propose fREX as an open framework for reverse engineering of executable behaviors from existing software code bases. fREX currently provides model discovery support for behavior embedded in Java code, employs the OMG's fUML standard language as executable pivot format for dynamic analysis, and uses model transformations to bridge Java and fUML. Thus, fREX also aims at contributing to explore the relationship between programming languages (e.g., Java) and executable mod-eling languages (e.g., fUML). In this paper, we describe the proposed fREX framework and its current reverse engineering support covering some core Java features. In addition we discuss how the framework can be used for performing different kinds of dynamic analysis on existing software, as well as how it could be extended in the future

SLO-ML:A Language for Service Level Objective Modelling in Multi-cloud applications

Cloud modelling languages (CMLs) are designed to assist customers in tackling the diversity of services in the current cloud market. While many CMLs have been proposed in the literature, they lack practical support for automating the selection of services based on the specific service level objectives of a customer's application. We put forward SLO-ML, a novel and generative CML to capture service level requirements. Subsequently, SLO-ML selects the services to honour the customer's requirements and generates the deployment code appropriate to these services. We present the architectural design of SLO-ML and the associated broker that realises the deployment operations. We evaluate SLO-ML using an experimental case study with a group of researchers and developers using a real-world cloud application. We also assess SLO-ML's overheads through empirical scalability tests. We express the promises of SLO-ML in terms of gained productivity and experienced usability, and we highlight its limitations by analysing it as application requirements grow

Cloud Modeling Languages by Example

Recently, several proposals towards a cloud modeling language have emerged. As they address the diversity of cloud environments, it is not surprising that these modeling languages support different scenarios. Using a by-example approach based on the scenario of software migration, we demonstrate their representational capabilities and review them according to characteristics common to all modeling languages as well as specific to the cloud computing domain. We report on our findings and present research guidelines for future efforts towards a better alignment of the different cloud modeling languages

UML Profile Generation for Annotation-based Modeling

The capability of UML profiles to serve as annotation mechanism has been recognized in both industry and research. With JUMP, we have presented a fully automatic approach to generate profiles from annotation-based Java libraries. We have demonstrated the practical value of JUMP by contributing profiles that facilitate reverse-engineering and forward-engineering scenarios for the Java platform. Its evaluation shows that automatically generated profiles are equal or even improved in quality compared to profiles currently used in practice

Bridging Java Annotations and UML Profiles with JUMP

UML profiles support annotations at the modeling level. However, current modeling tools lack the capabilities to generate such annotations required for the programming level, which is desirable for reverse engineering and for- ward engineering scenarios. To overcome this shortcoming, we defined an effec- tive conceptual mapping between Java annotations and UML profiles as a basis for implementing the JUMP tool. It automates the generation of profiles from annotation-based libraries and their application to generate profiled UML mod- els. In this demonstration, we (i) compare our mapping with the different rep- resentational capabilities of current UML modeling tools, (ii) apply our tool to a model-based software modernization scenario, and (iii) evaluate its scalability with real-world libraries and applications.publishe