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Towards a Deep Learning Architecture for software Models: An Initial Exploration 26

Towards a Deep Learning Architecture for Software Models: An...

26es Jornadas de Ingenieria del software y Bases de Datos, JISBD 2022 - 26th Conference on software engineering and Databases, JISBD 2022

作者： Mata, Luis Guerra, Esther de Lara, Juan Modelling & Software Engineering Research Group Universidad Autónoma de Madrid Spain

As in many other research areas, the use of Deep Learning (DL) techniques is growing in software engineering. However, these techniques are not yet widespread in the Model-Driven engineering (MDE) field. In this paper, we explore the use of DL to extract useful text embeddings out of software models. We propose a novel approach to embedding software models by means of transformer architectures trained on large datasets. Our approach combines intermediate representations and Language Models (LMs) to extract features from modelling artefacts in order to enable applications for intelligent model assistance, like model completion and correction. We show that the approach is potentially useful in MDE and may lead to useful results in the future. © 2022 26th Jornadas de Ingenieria del software y Bases de Datos, JISBD 2022. All Rights Reserved.

关键词： Embeddings

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Extensible Structural Analysis of Petri Net Product Lines 40th

Extensible Structural Analysis of Petri Net Product Lines

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40th International Conference on Application and Theory of Petri Nets and Concurrency, Petri Nets 2019, and 19th International Conference on Application of Concurrency to System Design, ACSD 2019

作者： Gómez-Martínez, Elena de Lara, Juan Guerra, Esther Modelling and Software Engineering Research Group Universidad Autónoma de Madrid C/ Francisco y Valiente 11 Madrid28049 Spain

ISBN: (纸本)9783662630785

Petri nets are a popular formalism to represent concurrent systems. However, their standard form does not offer variability support to model and effectively analyse large sets of variants of a given system. For this purpose, we propose a notion of product line of Petri nets to represent a set of similar concurrent systems. The formalization enriches Petri nets with a feature model characterizing the variability of the systems. Moreover, places, transitions and arcs can define presence conditions that determine the subset of system variants they belong to. To enable an efficient analysis of the set of all net variants, we have lifted several structural analysis methods for Petri nets, to the product line level. Currently, we support the lifted checking of the marked graph, state-machine, and (extended) free-choice properties, which avoids their analysis on each particular net of the product line in isolation. We demonstrate the feasibility of our proposal using examples in the domain of flexible assembly lines, and introduce an extensible tool infrastructure. The tool is based on Eclipse and FeatureIDE, and permits adding new analysis methods externally. Moreover, we present an evaluation that shows the efficiency gains of our method with respect to an enumerative approach that analyses the properties on every net within the product line separately. © 2021, Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Petri nets

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Seed Model Synthesis for Testing Model-Based Mutation Operators 1

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CAiSE Forum 2020, held as part of the 32nd International Conference on Advanced Information Systems engineering, CAiSE 2020

作者： Gómez-Abajo, Pablo Guerra, Esther de Lara, Juan Merayo, Mercedes G. Modelling and Software Engineering Group Universidad Autónoma de Madrid Madrid Spain Design and Testing of Reliable Systems Group Universidad Complutense de Madrid Madrid Spain

ISBN: (数字)9783030581350

ISBN: (纸本)9783030581343

In software engineering, mutation consists in injecting small changes in artefacts – like models, programs, or data – for purposes like (mutation) testing, test data generation, and all sorts of search-based methods. These activities normally require the definition of sets of mutation operators, which are often built ad-hoc because there is currently poor support for their development and testing. To improve this situation, in previous work we proposed a model-based approach to create and execute mutation operators. Our proposal represents the artefacts to be mutated as models and provides a domain-specific language called Wodel to define the mutation operators. However, testing the operators is cumbersome, since it requires the manual creation of input seed models. To facilitate this testing process, we propose a method – based on model finding – for the automated synthesis of test models that exercise the defined mutation operators. We provide tool support for our proposal, and illustrate its usage by defining mutation operators for BPMN. © 2020, Springer Nature Switzerland AG.

关键词： software testing

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Generalised tangent stabilised nonlinear elasticity: An automated framework for controlling material and geometric instabilities

arXiv

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arXiv 2024年

作者： Poya, Roman Ortigosa, Rogelio Gil, Antonio J. Kim, Theodore Bonet, Javier Meshing Framework Simulation & Test Solutions Siemens Digital Industries Software Cambridge United Kingdom Multiphysics Simulation and Optimization Lab Technical University of Cartagena Cartagena Murcia Spain Zienkiewicz Centre for Modelling Data and AI Faculty of Science and Engineering Swansea University Bay Campus United Kingdom Computer Graphics Group Yale School of Engineering & Applied Science Yale University New HavenCT United States Barcelona Spain

Tangent stabilised large strain isotropic elasticity was recently proposed by Poya et al. [1] wherein by working directly with principal stretches the entire eigenstructure of constitutive and geometric/initial stiffness terms were found in closed-form, giving fresh insights into exact convexity conditions of highly non-convex functions in discrete settings. Consequently, owing to these newly found tangent eigenvalues an analytic tangent stabilisation was proposed (for common non-convex strain energies that exhibit material and/or geometric instabilities) bypassing incumbent numerical approaches routinely used in nonlinear finite element analysis. This formulation appears to be extremely robust for quasi-static simulation of complex deformations even with no load increments and time stepping while still capturing instabilities (similar to dynamic analysis) automatically in ways that are infeasible for path-following techniques in practice. In this work, we generalise the notion of tangent stabilised elasticity to virtually all known invariant formulations of nonlinear elasticity. We show that, closed-form eigen-decomposition of tangents is easily available irrespective of invariant formulation or integrity basis. In particular, we work out closed-form tangent eigensystems for isotropic Total Lagrangian deformation gradient (F)-based and right Cauchy-Green (C)-based as well as Updated Lagrangian left Cauchy-Green (b)-based formulations and present their exact convexity conditions postulated in terms of their corresponding tangent and initial stiffness eigenvalues. In addition, we introduce the notion of geometrically stabilised polyconvex large strain elasticity for models that are materially stable but exhibit geometric instabilities for whom we construct their initial stiffness in a spectrally-decomposed form analytically. We further extend this framework to the case of transverse isotropy where once again, closed-form tangent eigensystems are found for common tran

关键词： Stiffness

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Artificial intelligence for modelling infectious disease epidemics

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Nature 2025年第8051期638卷 623-635页

作者： Kraemer, Moritz U. G. Tsui, Joseph L.-H. Chang, Serina Y. Lytras, Spyros Khurana, Mark P. Vanderslott, Samantha Bajaj, Sumali Scheidwasser, Neil Curran-Sebastian, Jacob Liam Semenova, Elizaveta Zhang, Mengyan Unwin, H. Juliette T. Watson, Oliver J. Mills, Cathal Dasgupta, Abhishek Ferretti, Luca Scarpino, Samuel V. Koua, Etien Morgan, Oliver Tegally, Houriiyah Paquet, Ulrich Moutsianas, Loukas Fraser, Christophe Ferguson, Neil M. Topol, Eric J. Duchêne, David A. Stadler, Tanja Kingori, Patricia Parker, Michael J. Dominici, Francesca Shadbolt, Nigel Suchard, Marc A. Ratmann, Oliver Flaxman, Seth Holmes, Edward C. Gomez-Rodriguez, Manuel Schölkopf, Bernhard Donnelly, Christl A. Pybus, Oliver G. Cauchemez, Simon Bhatt, Samir Pandemic Sciences Institute University of Oxford Oxford United Kingdom Department of Biology University of Oxford Oxford United Kingdom Department of Electrical Engineering and Computer Science University of California Berkeley Berkeley CA United States UCSF UC Berkeley Joint Program in Computational Precision Health Berkeley CA United States Division of Systems Virology Department of Microbiology and Immunology The Institute of Medical Science The University of Tokyo Tokyo Japan Section of Epidemiology Department of Public Health University of Copenhagen Copenhagen Denmark Oxford Vaccine Group University of Oxford and NIHR Oxford Biomedical Research Centre Oxford United Kingdom Department of Epidemiology and Biostatistics Imperial College London London United Kingdom Department of Computer Science University of Oxford Oxford United Kingdom School of Mathematics University of Bristol Bristol United Kingdom MRC Centre for Global Infectious Disease Analysis School of Public Health Imperial College London London United Kingdom Department of Statistics University of Oxford Oxford United Kingdom Doctoral Training Centre University of Oxford Oxford United Kingdom Institute for Experiential AI Northeastern University MA Boston Thailand Santa Fe Institute Santa Fe NM United States World Health Organization Regional Office for Africa Brazzaville Congo WHO Hub for Pandemic and Epidemic Intelligence Health Emergencies Programme World Health Organization Berlin Germany Centre for Epidemic Response and Innovation (CERI) School for Data Science and Computational Thinking Stellenbosch University Stellenbosch South Africa African Institute for Mathematical Sciences (AIMS) South Africa Muizenberg Cape Town South Africa Genomics England London United Kingdom Scripps Research La Jolla CA United States Department of Biosystems Science and Engineering ETH Zürich Basel Switzerland Swiss Institute of Bioinformatics Lausanne Switzerland The Ethox Centre Nuffield

Infectious disease threats to individual and public health are numerous, varied and frequently unexpected. Artificial intelligence (AI) and related technologies, which are already supporting human decision making in economics, medicine and social science, have the potential to transform the scope and power of infectious disease epidemiology. Here we consider the application to infectious disease modelling of AI systems that combine machine learning, computational statistics, information retrieval and data science. We first outline how recent advances in AI can accelerate breakthroughs in answering key epidemiological questions and we discuss specific AI methods that can be applied to routinely collected infectious disease surveillance data. Second, we elaborate on the social context of AI for infectious disease epidemiology, including issues such as explainability, safety, accountability and ethics. Finally, we summarize some limitations of AI applications in this field and provide recommendations for how infectious disease epidemiology can harness most effectively current and future developments in AI. © Springer Nature Limited 2025.

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A comparison of element agglomeration algorithms for unstructured geometric multigrid

arXiv

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arXiv 2020年

作者： Dargaville, Steven Buchan, A.G. Smedley-Stevenson, R.P. Smith, P.N. Pain, C.C. Applied Modelling and Computation Group Imperial College London SW7 2AZ United Kingdom School of Engineering and Materials Sciences Queen Mary University of London E14 NS United Kingdom AWE Aldermaston ReadingRG7 4PR United Kingdom ANSWERS Software Service Jacobs Kimmeridge House Dorset Green Technology Park DorchesterDT2 8ZB United Kingdom

This paper compares the performance of seven different element agglomeration algorithms on unstructured triangular/tetrahedral meshes when used as part of a geometric multigrid. Five of these algorithms come from the literature on AMGe multigrid and mesh partitioning methods. The resulting multigrid schemes are tested matrix-free on two problems in 2D and 3D taken from radiation transport applications;one of which is in the diffusion limit. In two dimensions all coarsening algorithms result in multigrid methods which perform similarly, but in three dimensions aggressive element agglomeration performed by METIS produces the shortest runtimes and multigrid setup times. Copyright © 2020, The Authors. All rights reserved.

关键词： Coarsening

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Angular adaptivity with filtered Pn methods

Angular adaptivity with filtered Pn methods

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2019 Transactions of the American Nuclear Society, ANS 2019

作者： Dargaville, S. Buchan, A.G. Smedley-Stevenson, R.P. Smith, P.N. Pain, C.C. Applied Modelling and Computation Group Imperial College London SW7 2AZ United Kingdom School of Engineering and Material Sciences Queen Mary University of London E14 NS United Kingdom AWE Aldermaston ReadingRG7 4PR United Kingdom ANSWERS Software Service Wood PLC Kimmeridge House Dorset Green Technology Park DorchesterDT2 8ZB United Kingdom

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JAVACHECK: A domain specific language for the static analysis of Java code

JAVACHECK: A domain specific language for the static analysi...

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2017 MODELS Satellite Event: Workshops (ModComp, ME, EXE, COMMitMDE, MRT, MULTI, GEMOC, MoDeVVa, MDETools, FlexMDE, MDEbug), Posters, Doctoral Symposium, Educator Symposium, ACM Student Research Competition, and Tools and Demonstrations, MODEL-SSE 2017

作者： Pérez-Soler, Sara De Lara, Juan Modelling and Software Engineering Research Group Computer Science Department Universidad Autónoma de Madrid Spain

The increasing complexity of software systems has raised the need for code analysis tools to assess its quality. However, these tools offer predefined metrics or evaluation criteria, which are frequently hard to extend or modify. For this purpose, we have developed JAVACHECK, a Domain-Specific Language targeted to define expected properties of Java code bases. JAVACHECK can be used in a variety of scenarios related to quality assurance: to define expected code styles (e.g., naming conventions), specify programming conventions (e.g., private attributes), detect code smells possibly indicating errors (e.g., equals method with no hashCode), and detect patterns (e.g., uses of Singleton) or requirements demanded in a project (e.g., a class with name synonym to "Professor").

关键词： Static analysis

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Assisted modelling over social networks with SOCIO

Assisted modelling over social networks with SOCIO

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作者： Pérez-Soler, Sara Guerra, Esther De Lara, Juan Modelling and Software Engineering Research Group Computer Science Department Universidad Autónoma de Madrid Spain

Social networks are intensively used nowadays for both leisure and work. They have become a natural communication mechanism which helps users in coordinating and collaborating in their daily life activities. To profit from their pervasive use, we propose SOCIO: a modelling assistant that seamlessly integrates across several social networks, like Telegram or Twitter. SOCIO is a modelling bot that can interpret natural language sentences and create meta-models out of them. It provides traceability of design decisions and statistics of user contributions. A video showcasing the tool is available at https://***/modellingBot/.

关键词： Leisure

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Angular adaptivity with spherical harmonics for Boltzmann transport

arXiv

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arXiv 2019年

This paper describes an angular adaptivity algorithm for Boltzmann transport applications which uses Pn and filtered Pn expansions, allowing for different expansion orders across space/energy. Our spatial discretisation is specifically designed to use less memory than competing DG schemes and also gives us direct access to the amount of stabilisation applied at each node. For filtered Pn expansions, we then use our adaptive process in combination with this net amount of stabilisation to compute a spatially dependent filter strength that does not depend on a priori spatial information. This applies heavy filtering only where discontinuities are present, allowing the filtered Pn expansion to retain high-order convergence where possible. Regular and goal-based error metrics are shown and both the adapted Pn and adapted filtered Pn methods show significant reductions in DOFs and runtime. The adapted filtered Pn with our spatially dependent filter shows close to fixed iteration counts and up to high-order is even competitive with P0 discretisations in problems with heavy advection. Copyright © 2019, The Authors. All rights reserved.

关键词： Stabilization

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