Using Conceptual Modeling for Designing Multi-View Modeling Tools

Multi-view modeling methods (MVMM) can cope with the increasing complexity of today\u27s enterprise and information systems by decomposing the corresponding model into several viewpoints. The combination of the instantiated views gives the whole model of the system. Modeling tools are vital for efficient utilization of MVMMs. However, sufficient support in the conceptual design of multi-view modeling tools is not given. The paper at hand introduces the MuVieMoT modeling method, dedicated towards the conceptualization of multi-view modeling tools. The method is focused on how to capture, with conceptual modeling means, the constituents of MVMMs, in terms of viewpoints, modeling procedure and consistency mechanisms specification. The method is aimed at method engineers and tool developers, bridging the gap between tool design and tool development. Applicability of the method is illustrated by a case study, hereby defining the conceptual design of a multi-view modeling tool for an enterprise modeling method

Multi-view approaches for software and system modelling: a systematic literature review

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4th Workshop on View-Based, Aspect-Oriented and Orthographic Software Modelling : Proceedings, 2 March 2016, Karlsruhe, Germany

Modern software engineering paradigms, such as model-driven development, multi-view modelling, or role-based software development, use different types and combinations of abstraction techniques to decompose systems into human-tractable pieces. This leads to an increasing number of models and views that have to be considered, which presents fundamental challenges for engineers of complex softwareintensive systems. Software developers need technologies for operationally managing views of systems in a consistent way, and software architects require concepts that indicate in which way views and models should be developed, evolved, and navigated as projects evolve. The goal of this workshop is to distil a common understanding of existing approaches and current research directions in treating heterogeneous models of software and systems

A Development Method for the Conceptual Design of Multi-View Modeling Tools with an Emphasis on Consistency Requirements

The main objective of this thesis is to bridge the gap between modeling method experts on the one side and tool developers on the other. More precisely, the focus is on the specification of requirements for multi-view modeling tools. In this regard, the thesis introduces a methodological approach that supports the specification of conceptual designs for multi-view modeling tools in a stepwise manner: the MuVieMoT approach. MuVieMoT utilizes generic multi-view modeling concepts and the model-driven engineering paradigm to establish an overarching specification of multi-view modeling tools with an emphasis on consistency requirements. The approach builds on and extends the theoretical foundation of metamodeling and multi-view modeling: generic multi-view modeling concepts, integrated multi-view modeling approaches, and possibilities for formalized modeling method specifications. Applicability and utility of MuVieMoT are evaluated using an illustrative scenario, therefore specifying a conceptual design for a multi-view modeling tool for the Semantic Object Model enterprise modeling method. The thesis moreover introduces the MuVieMoT modeling environment, enabling the efficient application of the approach as well as the model-driven development of initial multi-view modeling tools based on the conceptual models created with MuVieMoT. Consequently, the approach fosters an intersubjective and unambiguous understanding of the tool requirements between method experts and tool developers

A decision-making Support system for Enterprise Architecture Modelling

Companies are increasingly conscious of the importance of Enterprise Architecture (EA) to represent and manage IT and business in a holistic way. EA modelling has become decisive to achieve models that accurately represents behaviour and assets of companies and lead them to make appropriate business decisions. Although EA representations can be manually modelled by experts, automatic EA modelling methods have been proposed to deal with drawbacks of manual modelling, such as error-proneness, time-consumption, slow and poor readaptation, and cost. However, automatic modelling is not effective for the most abstract concepts in EA like strategy or motivational aspects. Thus, companies are demanding hybrid approaches that combines automatic with manual modelling. In this context there are no clear relationships between the input artefacts (and mining techniques) and the target EA viewpoints to be automatically modelled, as well as relationships between the experts' roles and the viewpoints to which they might contribute in manual modelling. Consequently, companies cannot make informed decisions regarding expert assignments in EA modelling projects, nor can they choose appropriate mining techniques and their respective input artefacts. This research proposes a decision support system whose core is a genetic algorithm. The proposal first establishes (based on a previous literature review) the mentioned missing relationships and EA model specifications. Such information is then employed using a genetic algorithm to decide about automatic, manual or hybrid modelling by selecting the most appropriate input artefacts, mining techniques and experts. The genetic algorithm has been optimized so that the system aids EA architects to maximize the accurateness and completeness of EA models while cost (derived from expert assignments and unnecessary automatic generations) are kept under control

Realizing Change-Driven Consistency for Component Code, Architectural Models, and Contracts in Vitruvius

During the development of component-based software systems, it is often impractical or even impossible to include all development information into the source code. Instead, specialized languages are used to describe components and systems on different levels of abstraction or from different viewpoints: Component-based architecture models and contracts, for example, can be used to describe the system on a high level of abstraction, and to formally specify component constraints. Since models, contracts, and code contain redundant information, inconsistencies can occur if they are modified independently. Keeping this information consistent manually can require considerable effort, and can lead to costly errors, for example, when security-relevant components are verified against inconsistent contracts. In this technical report, we present details on realizing an approach for keeping component-based architecture models and contracts specified in the Java Modeling Language (JML) consistent with Java source code. We use change-driven incremental transformations and the Vitruvius framework to automate the consistency preservation where this is possible. Using two case studies, we demonstrate how to detect and propagate changes and refactoring operations to keep models and contracts consistent with the source code

Flexible Views for View-Based Model-Driven Development

ABSTRACT Model-driven development processes suffer from growing complexity, which leads to information spread across heterogeneous metamodels as well as drift and erosion between architecture and implementation. In this paper, we present a view-based modeling approach based on Orthographic Software Modeling (OSM), and introduce flexible views as a concept for the creation of custom, user-specific views. The envisioned benefit of the approach is to improve software quality, to increase consistency between the various modeling artifacts in model-driven software development, and to reduce the complexity for software developers

A NLP Pipeline for the Automatic Extraction of a Complete Microorganism’s Picture from Microbiological Notes

The Italian “Istituto Superiore di Sanità” (ISS) identifies hospital-acquired infections (HAIs) as the most frequent and serious complications in healthcare. HAIs constitute a real health emergency and, therefore, require decisive action from both local and national health organizations. Information about the causative microorganisms of HAIs is obtained from the results of microbiological cultures of specimens collected from infected body sites, but microorganisms’ names are sometimes reported only in the notes field of the culture reports. The objective of our work was to build a NLP-based pipeline for the automatic information extraction from the notes of microbiological culture reports. We analyzed a sample composed of 499 texts of notes extracted from 1 month of anonymized laboratory referral. First, our system filtered texts in order to remove nonmeaningful sentences. Thereafter, it correctly extracted all the microorganisms’ names according to the expert’s labels and linked them to a set of very important metadata such as the translations into national/international vocabularies and standard definitions. As the major result of our pipeline, the system extracts a complete picture of the microorganism