A-posteriori Typing for Model-Driven Engineering

Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. J. de Lara, E. Guerra and J. Sánchez Cuadrado, "A-posteriori typing for Model-Driven Engineering," 2015 ACM/IEEE 18th International Conference on Model Driven Engineering Languages and Systems (MODELS), Ottawa, ON, 2015, pp. 156-165. doi: 10.1109/MODELS.2015.7338246Model-Driven Engineering is founded on the ability to create and process models conformant to a meta-model. Hence, meta-model classes are used in two ways: as templates to create objects, and as classifiers for them. While these two aspects are inherently tied in most meta-modelling approaches, in this paper, we discuss the benefits of their decoupling. Thus, we rely on standard mechanisms for object creation and propose a-posteriori typing as a means to reclassify objects and enable multiple, partial, dynamic typings. This approach enhances flexibility, permitting unanticipated reutilization (as existing model management operations defined for a meta-model can be reused with other models once they get reclassified), as well as model transformation by reclassification.We show the underlying theory behind the introduced concepts, and illustrate its applicability using our METADEPTH meta-modelling tool.Work supported by the Spanish MINECO (TIN2011-24139 and TIN2014-52129-R), and the R&D programme of the Madrid Region (S2013/ICE-3006)

Quick fixing ATL model transformations

Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. J. Sánchez Cuadrado, E. Guerra and J. de Lara, "Quick fixing ATL model transformations," Model Driven Engineering Languages and Systems (MODELS), 2015 ACM/IEEE 18th International Conference on, Ottawa, ON, 2015, pp. 146-155. doi: 10.1109/MODELS.2015.7338245The correctness of model transformations is key to obtain reliable MDE solutions. However, current transformation tools provide limited support to statically detect and correct errors. This way, the identification of errors and their correction are mostly manual activities. Our aim is to improve this situation. Based on a static analyser for ATL model transformations which we have previously built, we present a method and a system to propose quick fixes for transformation errors. The analyser is based on a combination of program analysis and constraint solving, and our quick fix generation technique makes use of the analyser features to provide a range of fixes, notably some nontrivial, transformation-specific ones. Our approach integrates seamlessly with the ATL editor. We provide an evaluation based on an existing faulty transformation, and automatically generated transformation mutants, showing overall good results.Work supported by the Spanish MINECO (TIN2011-24139 and TIN2014-52129-R), the R&D programme of the Madrid Region (S2013/ICE-3006), and the EU commission (FP7-ICT-2013-10, #611125)

Reusable abstractions for modeling languages

This is the author’s version of a work that was accepted for publication in Information Systems. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Information Systems, 38, 8, (2013) DOI: 10.1016/j.is.2013.06.001Model-driven engineering proposes the use of models to describe the relevant aspects of the system to be built and synthesize the final application from them. Models are normally described using Domain-Specific Modeling Languages (DSMLs), which provide primitives and constructs of the domain. Still, the increasing complexity of systems has raised the need for abstraction techniques able to produce simpler versions of the models while retaining some properties of interest. The problem is that developing such abstractions for each DSML from scratch is time and resource consuming. In this paper, our goal is reducing the effort to provide modeling languages with abstraction mechanisms. For this purpose, we have devised some techniques, based on generic programming and domain-specific meta-modeling, to define generic abstraction operations that can be reused over families of modeling languages sharing certain characteristics. Abstractions can make use of clustering algorithms as similarity criteria for model elements. These algorithms can be made generic as well, and customized for particular languages by means of annotation models. As a result, we have developed a catalog of reusable abstractions using the proposed techniques, together with a working implementation in the MetaDepth multi-level meta-modeling tool. Our techniques and prototypes demonstrate that it is feasible to build reusable and adaptable abstractions, so that similar abstractions need not be developed from scratch, and their integration in new or existing modeling languages is less costly.Work funded by the Spanish Ministry of Economy and Competitivity with project “Go Lite” (TIN2011-24139), and the R&D programme of Madrid Region with project “eMadrid” (S2009/TIC-1650)

Quick xing ATL transformations with speculative analysis

Model transformations are central compo- nents of most model-based software projects. While en- suring their correctness is vital to guarantee the quality of the solution, current transformation tools provide lim- ited support to statically detect and x errors. In this way, the identi cation of errors and their correction are nowadays mostly manual activities which incur in high costs. The aim of this work is to improve this situation. Recently, we developed a static analyser that com- bines program analysis and constraint solving to iden- tify errors in ATL model transformations. In this paper, we present a novel method and system that uses our analyser to propose suitable quick xes for ATL transfor- mation errors, notably some non-trivial, transformation- speci c ones. Our approach supports speculative analy- sis to help developers select the most appropriate x by creating a dynamic ranking of xes, reporting on the consequences of applying a quick x, and providing a previsualization of each quick x application. The approach integrates seamlessly with the ATL ed- itor. Moreover, we provide an evaluation based on exist- ing faulty transformations built by a third party, and on automatically generated transformation mutants, which are then corrected with the quick xes of our catalogueWork supported by the Spanish Ministry of Economyand Competitivity (TIN2014-52129-R), the R&D programme of the Madrid Region (S2013/ICE-3006), and the EU commission (FP7-ICT-2013-10, #611125

Facet-oriented Modelling

© ACM 2021. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in ACM Transactions on Software Engineering and Methodology, http://dx.doi.org/10.1145/10.1145/3428076Models are the central assets in model-driven engineering (MDE), as they are actively used in all phases of software development. Models are built using metamodel-based languages, and so objects in models are typed by a metamodel class. This typing is static, established at creation time, and cannot be changed later. Therefore, objects in MDE are closed and fixed with respect to the class they conform to, the fields they have, and the well-formedness constraints they must comply with. This hampers many MDE activities, like the reuse of model-related artefacts such as transformations, the opportunistic or dynamic combination of metamodels, or the dynamic reconfiguration of models. To alleviate this rigidity, we propose making model objects open so that they can acquire or drop so-called facets. These contribute with a type, fields and constraints to the objects holding them. Facets are defined by regular metamodels, hence being a lightweight extension of standard metamodelling. Facet metamodels may declare usage interfaces, as well as laws that govern the assignment of facets to objects (or classes). This article describes our proposal, reporting on a theory, analysis techniques, and an implementation. The benefits of the approach are validated on the basis of five case studies dealing with annotation models, transformation reuse, multi-view modelling, multi-level modelling, and language product linesWork partially funded by the R&D programme of the Madrid Region (project FORTE, S2018/TCS-4314) and the Spanish Ministry of Science (project MASSIVE, RTI2018-095255-B-I00

Mobile Phone Apps for Quality of Life and Well-Being Assessment in Breast and Prostate Cancer Patients: Systematic Review

Background: Mobile phone health apps are increasingly gaining attention in oncological care as potential tools for supporting cancer patients. Although the number of publications and health apps focusing on cancer is increasing, there are still few specifically designed for the most prevalent cancers diagnosed: breast and prostate cancers. There is a need to review the effect of these apps on breast and prostate cancer patients’ quality of life (QoL) and well-being. Objective: The purposes of this study were to review the scientific literature on mobile phone apps targeting breast or prostate cancer patients and involving QoL and well-being (anxiety and depression symptoms) and analyze the clinical and technological characteristics, strengths, and weaknesses of these apps, as well as patients’ user experience with them. Methods: We conducted a systematic review of peer-reviewed literature from The Cochrane Library, Excerpta Medica Database, PsycINFO, PubMed, Scopus, and MEDLINE to identify studies involving apps focused on breast and/or prostate cancer patients and QoL and/or well-being published between January 1, 2000, and July 12, 2017. Only trial studies which met the inclusion criteria were selected. The systematic review was completed with a critical analysis of the apps previously identified in the health literature research that were available from the official app stores. Results: The systematic review of the literature yielded 3862 articles. After removal of duplicates, 3229 remained and were evaluated on the basis of title and abstract. Of these, 3211 were discarded as not meeting the inclusion criteria, and 18 records were selected for full text screening. Finally, 5 citations were included in this review, with a total of 644 patients, mean age 52.16 years. Four studies targeted breast cancer patients and 1 focused on prostate cancer patients. Four studies referred to apps that assessed QoL. Only 1 among the 5 analyzed apps was available from the official app store. In 3 studies, an app-related intervention was carried out, and 2 of them reported an improvement on QoL. The lengths of the app-related interventions varied from 4 to 12 weeks. Because 2 of the studies only tracked use of the app, no effect on QoL or well-being was found. Conclusions: Despite the existence of hundreds of studies involving cancer-focused mobile phone apps, there is a lack of rigorous trials regarding the QoL and/or well-being assessment in breast and/or prostate cancer patients. A strong and collective effort should be made by all health care providers to determine those cancer-focused apps that effectively represent useful, accurate, and reliable tools for cancer patients’ disease management.European Union's Horizon 2020 No 72201

Wodel-Edu: a tool for the generation and evaluation of diagram-based exercises

Creating and grading exercises are recurring tasks within higher education. When these exercises are based on diagrams – like logic circuits, automata or class diagrams – we can represent them as models, and use model-driven engineering techniques for the large-scale generation of quizzes, which can be automatically graded. This way, we propose a domain-independent tool for the generation and automated evaluation of diagram-based exercises called WODEL-EDU. WODEL-EDU is built atop WODEL, an extensible tool for model mutation, and offers seven kinds of diagram exercises. It supports code generation from the exercises for the MOODLE platform, the web, ANDROID and IOS applications. Evaluations from the professor and student perspectives show good resultsSpecial gratitude to Andrés Rico-Fernández and Jaime Velázquez Pazos for their help with the WODEL-EDU implementation, building the code generators for the ANDROID and IOS exercises applications, respectively, and to all participants in the evaluation. Project partially funded by the Spanish MICINN (PID2021-122270OB-I00, TED2021-129381B-C21

Automated generation and correction of diagram-based exercises for Moodle

One of the most time‐consuming task for teachers is creating and correcting exercises to evaluate students. This is normally performed by hand, which incurs high time costs and is error‐prone. A way to alleviate this problem is to provide an assistant tool that automates such tasks. In the case of exercises based on diagrams, they can be represented as models to enable their automated model‐based generation for any target environment, like web or mobile applications, or learning platforms like MOODLE. In this paper, we propose an automated process for synthesizing five types of diagram‐based exercises for the MOODLE platform. Being model‐based, our solution is domain‐agnostic (i.e., it can be applied to arbitrary domains like automata, electronics, or software design). We report on its use within a university course on automata theory, as well as evaluations of generality, effectiveness and efficiency, illustrating the benefits of our approachComunidad de Madrid, Grant/Award Number: S2018/TCS‐4314; Ministerio de Ciencia e Innovación, Grant/Award Numbers: PID2021‐ 122270OB‐I00, TED2021‐129381B‐C2

Property Satisfiability Analysis for Product Lines of Modelling Languages

© 2022 IEEE.  Personal use of this material is permitted.  Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Software engineering uses models throughout most phases of the development process. Models are defined using modelling languages. To make these languages applicable to a wider set of scenarios and customizable to specific needs, researchers have proposed using product lines to specify modelling language variants. However, there is currently a lack of efficient techniques for ensuring correctness with respect to properties of the models accepted by a set of language variants. This may prevent detecting problematic combinations of language variants that produce undesired effects at the model level. To attack this problem, we first present a classification of instantiability properties for language product lines. Then, we propose a novel approach to lifting the satisfiability checking of model properties of individual language variants, to the product line level. Finally, we report on an implementation of our proposal in the Merlin tool, and demonstrate the efficiency gains of our lifted analysis method compared to an enumerative analysis of each individual language variantThis work has been funded by the Spanish Ministry of Science (RTI2018-095255-B-I00), the R&D programme of Madrid (P2018/TCS-4314), and by NSERC. We thank the anonymous referees for their useful comment

Pattern-Based Development of Domain-Specific Modelling Languages

Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. A. Pescador, A. Garmendia, E. Guerra, J. Sánchez Cuadrado and J. de Lara, "Pattern-based development of Domain-Specific Modelling Languages," Model Driven Engineering Languages and Systems (MODELS), 2015 ACM/IEEE 18th International Conference on, Ottawa, ON, 2015, pp. 166-175. doi: 10.1109/MODELS.2015.7338247Model-Driven Engineering (MDE) promotes the use of models to conduct all phases of software development in an automated way. Models are frequently defined using Domain- Specific Modelling Languages (DSMLs), which many times need to be developed for the domain at hand. However, while constructing DSMLs is a recurring activity in MDE, there is scarce support for gathering, reusing and enacting knowledge for their design and implementation. This forces the development of every new DSML to start from scratch. To alleviate this problem, we propose the construction of DSMLs and their modelling environments aided by patterns which gather knowledge of specific domains, design alternatives, concrete syntax, dynamic semantics and functionality for the modelling environment. They may have associated services, realized via components. Our approach is supported by a tool that enables the construction of DSMLs through the application of patterns, and synthesizes a graphical modelling environment according to them.Work supported by the Spanish MINECO (TIN2011-24139 and TIN2014-52129-R), the R&D programme of the Madrid Region (S2013/ICE-3006), and the EU commission (FP7-ICT-2013-10, #611125)