117 research outputs found
Model-Agnostic process modelling
Modeling techniques in Business Process Management often suffer from low adoption due to the variety of profiles found in organizations. This project aims to provide a novel alternative to BPM documentation, ATD, based on annotated process descriptions in natural language
A Survey of Neural Trees
Neural networks (NNs) and decision trees (DTs) are both popular models of
machine learning, yet coming with mutually exclusive advantages and
limitations. To bring the best of the two worlds, a variety of approaches are
proposed to integrate NNs and DTs explicitly or implicitly. In this survey,
these approaches are organized in a school which we term as neural trees (NTs).
This survey aims to present a comprehensive review of NTs and attempts to
identify how they enhance the model interpretability. We first propose a
thorough taxonomy of NTs that expresses the gradual integration and
co-evolution of NNs and DTs. Afterward, we analyze NTs in terms of their
interpretability and performance, and suggest possible solutions to the
remaining challenges. Finally, this survey concludes with a discussion about
other considerations like conditional computation and promising directions
towards this field. A list of papers reviewed in this survey, along with their
corresponding codes, is available at:
https://github.com/zju-vipa/awesome-neural-treesComment: 35 pages, 7 figures and 1 tabl
Bridging the gap between textual and formal business process representations
Tesi en modalitat de compendi de publicacionsIn the era of digital transformation, an increasing number of organizations are start ing to think in terms of business processes. Processes are at the very heart of each business, and must be understood and carried out by a wide range of actors, from both technical and non-technical backgrounds alike.
When embracing digital transformation practices, there is a need for all involved parties to be aware of the underlying business processes in an organization. However, the representational complexity and biases of the state-of-the-art modeling notations pose a challenge in understandability. On the other hand, plain language representations, accessible by nature and easily understood by everyone, are often frowned upon by technical specialists due to their ambiguity.
The aim of this thesis is precisely to bridge this gap: Between the world of the techni cal, formal languages and the world of simpler, accessible natural languages. Structured as an article compendium, in this thesis we present four main contributions to address specific problems in the intersection between the fields of natural language processing and business process management.A l’era de la transformaciĂł digital, cada vegada mĂ©s organitzacions comencen a pensar en termes de processos de negoci. Els processos sĂłn el nucli principal de tota empresa i, com a tals, han de ser fĂ cilment comprensibles per un ampli ventall de rols, tant perfils tècnics com no-tècnics. Quan s’adopta la transformaciĂł digital, Ă©s necessari que totes les parts involucrades estiguin ben informades sobre els protocols implantats com a part del procĂ©s de digitalitzaciĂł. Tot i això, la complexitat i biaixos de representaciĂł dels llenguatges de modelitzaciĂł que actualment conformen l’estat de l’art sovint en dificulten la seva com prensiĂł. D’altra banda, les representacions basades en documentaciĂł usant llenguatge natural, accessibles per naturalesa i fĂ cilment comprensibles per tothom, moltes vegades sĂłn vistes com un problema pels perfils mĂ©s tècnics a causa de la presència d’ambigĂĽitats en els textos. L’objectiu d’aquesta tesi Ă©s precisament el de superar aquesta distĂ ncia: La distĂ ncia entre el mĂłn dels llenguatges tècnics i formals amb el dels llenguatges naturals, mĂ©s accessibles i senzills. Amb una estructura de compendi d’articles, en aquesta tesi presentem quatre grans lĂnies de recerca per adreçar problemes especĂfics en aquesta intersecciĂł entre les tecnologies d’anĂ lisi de llenguatge natural i la gestiĂł dels processos de negoci.Postprint (published version
Pattern-based refactoring in model-driven engineering
L’ingénierie dirigée par les modèles (IDM) est un paradigme du génie logiciel qui utilise les
modèles comme concepts de premier ordre à partir desquels la validation, le code, les tests
et la documentation sont dérivés. Ce paradigme met en jeu divers artefacts tels que les
modèles, les méta-modèles ou les programmes de transformation des modèles. Dans un
contexte industriel, ces artefacts sont de plus en plus complexes. En particulier, leur
maintenance demande beaucoup de temps et de ressources. Afin de réduire la complexité
des artefacts et le coût de leur maintenance, de nombreux chercheurs se sont intéressés au
refactoring de ces artefacts pour améliorer leur qualité.
Dans cette thèse, nous proposons d’étudier le refactoring dans l’IDM dans sa
globalité, par son application à ces différents artefacts. Dans un premier temps, nous
utilisons des patrons de conception spécifiques, comme une connaissance a priori, appliqués
aux transformations de modèles comme un véhicule pour le refactoring. Nous procédons
d’abord par une phase de détection des patrons de conception avec différentes formes et
différents niveaux de complétude. Les occurrences détectées forment ainsi des opportunités
de refactoring qui seront exploitées pour aboutir à des formes plus souhaitables et/ou plus
complètes de ces patrons de conceptions.
Dans le cas d’absence de connaissance a priori, comme les patrons de conception,
nous proposons une approche basée sur la programmation génétique, pour apprendre des
règles de transformations, capables de détecter des opportunités de refactoring et de les
corriger. Comme alternative à la connaissance disponible a priori, l’approche utilise des
exemples de paires d’artefacts d’avant et d’après le refactoring, pour ainsi apprendre les
règles de refactoring. Nous illustrons cette approche sur le refactoring de modèles.Model-Driven Engineering (MDE) is a software engineering paradigm that uses models as
first-class concepts from which validation, code, testing, and documentation are derived.
This paradigm involves various artifacts such as models, meta-models, or model
transformation programs. In an industrial context, these artifacts are increasingly complex.
In particular, their maintenance is time and resources consuming. In order to reduce the
complexity of artifacts and the cost of their maintenance, many researchers have been
interested in refactoring these artifacts to improve their quality.
In this thesis, we propose to study refactoring in MDE holistically, by its application
to these different artifacts. First, we use specific design patterns, as an example of prior
knowledge, applied to model transformations to enable refactoring. We first proceed with a
detecting phase of design patterns, with different forms and levels of completeness. The
detected occurrences thus form refactoring opportunities that will be exploited to implement
more desirable and/or more complete forms of these design patterns.
In the absence of prior knowledge, such as design patterns, we propose an approach
based on genetic programming, to learn transformation rules, capable of detecting
refactoring opportunities and correcting them. As an alternative to prior knowledge, our
approach uses examples of pairs of artifacts before and after refactoring, in order to learn
refactoring rules. We illustrate this approach on model refactoring
National freight transport planning: towards a Strategic Planning Extranet Decision Support System (SPEDSS)
This thesis provides a `proof-of-concept' prototype and a design architecture for a
Object Oriented (00) database towards the development of a Decision Support
System (DSS) for the national freight transport planning problem. Both governments
and industry require a Strategic Planning Extranet Decision Support System
(SPEDSS) for their effective management of the national Freight Transport Networks
(FTN).
This thesis addresses the three key problems for the development of a SPEDSS to
facilitate national strategic freight planning: 1) scope and scale of data available and
required; 2) scope and scale of existing models; and 3) construction of the software.
The research approach taken embodies systems thinking and includes the use of:
Object Oriented Analysis and Design (OOA/D) for problem encapsulation and
database design; artificial neural network (and proposed rule extraction) for
knowledge acquisition of the United States FTN data set; and an iterative Object
Oriented (00) software design for the development of a `proof-of-concept'
prototype. The research findings demonstrate that an 00 approach along with the use
of 00 methodologies and technologies coupled with artificial neural networks
(ANNs) offers a robust and flexible methodology for the analysis of the FTN problem
domain and the design architecture of an Extranet based SPEDSS.
The objectives of this research were to: 1) identify and analyse current problems and
proposed solutions facing industry and governments in strategic transportation
planning; 2) determine the functional requirements of an FTN SPEDSS; 3) perform a
feasibility analysis for building a FTN SPEDSS `proof-of-concept' prototype and
(00) database design; 4) develop a methodology for a national `internet-enabled'
SPEDSS model and database; 5) construct a `proof-of-concept' prototype for a
SPEDSS encapsulating identified user requirements; 6) develop a methodology to
resolve the issue of the scale of data and data knowledge acquisition which would act
as the `intelligence' within a SPDSS; 7) implement the data methodology using
Artificial Neural Networks (ANNs) towards the validation of it; and 8) make recommendations for national freight transportation strategic planning and further
research required to fulfil the needs of governments and industry.
This thesis includes: an 00 database design for encapsulation of the FTN; an
`internet-enabled' Dynamic Modelling Methodology (DMM) for the virtual
modelling of the FTNs; a Unified Modelling Language (UML) `proof-of-concept'
prototype; and conclusions and recommendations for further collaborative research
are identified
Search-based system architecture development using a holistic modeling approach
This dissertation presents an innovative approach to system architecting where search algorithms are used to explore design trade space for good architecture alternatives. Such an approach is achieved by integrating certain model construction, alternative generation, simulation, and assessment processes into a coherent and automated framework. This framework is facilitated by a holistic modeling approach that combines the capabilities of Object Process Methodology (OPM), Colored Petri Net (CPN), and feature model. The resultant holistic model can not only capture the structural, behavioral, and dynamic aspects of a system, allowing simulation and strong analysis methods to be applied, it can also specify the architectural design space. Both object-oriented analysis and design (OOA/D) and domain engineering were exploited to capture design variables and their domains and define architecture generation operations. A fully realized framework (with genetic algorithms as the search algorithm) was developed. Both the proposed framework and its suggested implementation, including the proposed holistic modeling approach and architecture alternative generation operations, are generic. They are targeted at systems that can be specified using object-oriented or process-oriented paradigm. The broad applicability of the proposed approach is demonstrated on two examples. One is the configuration of reconfigurable manufacturing systems (RMSs) under multi-objective optimization and the other is the architecture design of a manned lunar landing system for the Apollo program. The test results show that the proposed approach can cover a huge number of architecture alternatives and support the assessment of several performance measures. A set of quality results was obtained after running the optimization algorithm following the proposed framework --Abstract, page iii
Evolution of web-based systems in model driven architecture
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