47 research outputs found
A DSDEVS-Based Model for Verifying Structural Constraints in Dynamic Business Processes
This paper presents a DSDEVS-based model âDynamic Structure Discrete Event System specificationâ for modeling and simulating business processes with dynamic structure regarding to different contexts. Consequently, this model, formally, improves the reuse of configurable business processes. Thus, the proposed model allows the analysts to personalize their configurable business processes in a sound manner by verifying a set of structure properties, such as, the lack of synchronization and the deadlock by means of simulation. The implementation was done in DEVS-Suite simulator, which is based on DEVSJAVA models
Toward overcoming accidental complexity in organisational decision-making
This paper takes a practitioner's perspective on the problem of organisational decision-making. Industry practice follows a refinement based iterative method for organizational decision-making. However, existing enterprise modelling tools are not complete with respect to the needs of organizational decision-making. As a result, today, a decision maker is forced to use a chain of non-interoperable tools supporting paradigmatically diverse modelling languages with the onus of their co-ordinated use lying entirely on the decision maker. This paper argues the case for a model-based approach to overcome this accidental complexity. A bridge meta-model, specifying relationships across models created by individual tools, ensures integration and a method, describing what should be done when and how, and ensures better tool integration. Validation of the proposed solution using a case study is presented with current limitations and possible means of overcoming them outlined
Actor based behavioural simulation as an aid for organisational decision making
Decision-making is a critical activity for most of the modern organizations to stay competitive in rapidly changing business environment. Effective organisational decision-making requires deep understanding of various organisational aspects such as its goals, structure, business-as-usual operational processes, environment where it operates, and inherent characteristics of the change drivers that may impact the organisation. The size of a modern organisation, its socio-technical characteristics, inherent uncertainty, volatile operating environment, and prohibitively high cost of the incorrect decisions make decision-making a challenging endeavor.
While the enterprise modelling and simulation technologies have evolved into a mature discipline for understanding a range of engineering, defense and control systems, their application in organisational decision-making is considerably low. Current organisational decision-making approaches that are prevalent in practice are largely qualitative. Moreover, they mostly rely on human experts who are often aided with the primitive technologies such as spreadsheets and
visual diagrams.
This thesis argues that the existing modelling and simulation technologies are neither suitable to represent organisation and decision artifacts in a comprehensive and machine-interpretable form nor do they comprehensively address the analysis needs. An approach that advances the modelling abstraction and analysis machinery for organisational decision-making is proposed. In particular, this thesis proposes a domain specific language to represent relevant aspects of an organisation for decision-making, establishes the relevance of a bottom-up simulation technique as a means for analysis, and introduces a method to utilise the proposed modelling abstraction, analysis technique, and analysis machinery in an effective and convenient manner
Digital twin as risk-free experimentation aid for techno-socio-economic systems
Environmental uncertainties and hyperconnectivity force techno-socio-economic systems to introspect and adapt to succeed and survive. Current practice is chiefly intuition-driven which is inconsistent with the need for precision and rigor. We propose that this can be addressed through the use of digital twins by combining results from Modelling & Simulation, Artificial Intelligence, and Control Theory to create a risk free âin silicoâ experimentation aid to help: (i) understand why system is the way it is, (ii) be prepared for possible outlier conditions, and (iii) identify plausible solutions for mitigating the outlier conditions in an evidence-backed manner. We use reinforcement learning to systematically explore the digital twin solution space. Our proposal is significant because it advances the effective use of digital twins to new problem domains that have greater impact potential. Our novel approach contributes a meta model for simulatable digital twin of industry scale techno-socio-economic systems, agent-based implementation of the digital twin, and an architecture that serves as a risk-free experimentation aid to support simulation-based evidence-backed decision-making. We also discuss validation of this approach, associated technology infrastructure, and architecture through a representative sample of industry-scale real-world use cases
ICSEA 2021: the sixteenth international conference on software engineering advances
The Sixteenth International Conference on Software Engineering Advances (ICSEA 2021), held on October 3 - 7, 2021 in Barcelona, Spain, continued a series of events covering a broad spectrum of software-related topics.
The conference covered fundamentals on designing, implementing, testing, validating and maintaining various kinds of software. The tracks treated the topics from theory to practice, in terms of methodologies, design, implementation, testing, use cases, tools, and lessons learnt. The conference topics covered classical and advanced methodologies, open source, agile software, as well as software deployment and software economics and education.
The conference had the following tracks:
Advances in fundamentals for software development
Advanced mechanisms for software development
Advanced design tools for developing software
Software engineering for service computing (SOA and Cloud)
Advanced facilities for accessing software
Software performance
Software security, privacy, safeness
Advances in software testing
Specialized software advanced applications
Web Accessibility
Open source software
Agile and Lean approaches in software engineering
Software deployment and maintenance
Software engineering techniques, metrics, and formalisms
Software economics, adoption, and education
Business technology
Improving productivity in research on software engineering
Trends and achievements
Similar to the previous edition, this event continued to be very competitive in its selection process and very well perceived by the international software engineering community. As such, it is attracting excellent contributions and active participation from all over the world. We were very pleased to receive a large amount of top quality contributions.
We take here the opportunity to warmly thank all the members of the ICSEA 2021 technical program committee as well as the numerous reviewers. The creation of such a broad and high quality conference program would not have been possible without their involvement. We also kindly thank all the authors that dedicated much of their time and efforts to contribute to the ICSEA 2021. We truly believe that thanks to all these efforts, the final conference program consists of top quality contributions.
This event could also not have been a reality without the support of many individuals, organizations and sponsors. We also gratefully thank the members of the ICSEA 2021 organizing committee for their help in handling the logistics and for their work that is making this professional meeting a success.
We hope the ICSEA 2021 was a successful international forum for the exchange of ideas and results between academia and industry and to promote further progress in software engineering research
Framework for collaborative knowledge management in organizations
Nowadays organizations have been pushed to speed up the rate of industrial transformation to high value products and services. The capability to agilely respond to new market demands became a strategic pillar for innovation, and knowledge management could support organizations to achieve that goal. However, current knowledge management approaches tend to be over complex or too academic, with interfaces difficult to manage, even more if cooperative handling is required. Nevertheless, in an ideal framework, both tacit and explicit knowledge management should be addressed to achieve knowledge handling with precise and semantically meaningful definitions. Moreover, with the increase of Internet usage, the amount of available information explodes. It leads to the observed progress in the creation of mechanisms to retrieve useful knowledge from the huge existent amount of information sources. However, a same knowledge representation of a thing could mean differently to different people and applications.
Contributing towards this direction, this thesis proposes a framework capable of gathering the knowledge held by domain experts and domain sources through a knowledge management system and transform it into explicit ontologies. This enables to build tools with advanced reasoning capacities with the aim to support enterprises decision-making processes. The author also intends to address the problem of knowledge transference within an among organizations. This will be done through a module (part of the proposed framework) for domainâs lexicon establishment which purpose is to represent and unify the understanding of the domainâs used semantic
Multi-paradigm modelling for cyberâphysical systems: a descriptive framework
The complexity of cyberâphysical systems (CPSS) is commonly addressed through complex workflows, involving models in a plethora of different formalisms, each with their own methods, techniques, and tools. Some workflow patterns, combined with particular types of formalisms and operations on models in these formalisms, are used successfully in engineering practice. To identify and reuse them, we refer to these combinations of workflow and formalism patterns as modelling paradigms. This paper proposes a unifying (Descriptive) Framework to describe these paradigms, as well as their combinations. This work is set in the context of Multi-Paradigm Modelling (MPM), which is based on the principle to model every part and aspect of a system explicitly, at the most appropriate level(s) of abstraction, using the most appropriate modelling formalism(s) and workflows. The purpose of the Descriptive Framework presented in this paper is to serve as a basis to reason about these formalisms, workflows, and their combinations. One crucial part of the framework is the ability to capture the structural essence of a paradigm through the concept of a paradigmatic structure. This is illustrated informally by means of two example paradigms commonly used in CPS: Discrete Event Dynamic Systems and Synchronous Data Flow. The presented framework also identifies the need to establish whether a paradigm candidate follows, or qualifies as, a (given) paradigm. To illustrate the ability of the framework to support combining paradigms, the paper shows examples of both workflow and formalism combinations. The presented framework is intended as a basis for characterisation and classification of paradigms, as a starting point for a rigorous formalisation of the framework (allowing formal analyses), and as a foundation for MPM tool development
Monitoring of Honey Bee Colony Losses
In recent decades, independent national and international research programs have revealed possible reasons behind the death of managed honey bee colonies worldwide. Such losses are not due to a single factor, but instead are due to highly complex interactions between various internal and external influences, including pests, pathogens, honey bee stock diversity, and environmental changes. Reduced honey bee vitality and nutrition, exposure to agrochemicals, and the quality of colony management contribute to reduced colony survival in beekeeping operations. Our Special Issue (SI) on ââMonitoring of Honey Bee Colony Lossesâ aims to address the specific challenges that honey bee researchers and beekeepers face. This SI includes four reviews, with one being a meta-analysis that identifies gaps in the current and future directions for research into honey bee coloniesâ mortalities. Other review articles include studies regarding the impact of numerous factors on honey bee mortality, including external abiotic factors (e.g., winter conditions and colony management) as well as biotic factors such as attacks by Vespa velutina and Varroa destructor