Adding Executable Context to Executable Architectures: Enabling an Executable Context Simulation Framework (ECSF)

A system that does not stand alone is represented by a complex entity of component combinations that interact with each other to execute a function. In today\u27s interconnected world, systems integrate with other systems - called a system-of-systems infrastructure: a network of interrelated systems that can often exhibit both predictable and unpredictable behavior. The current state-of-the-art evaluation process of these system-of-systems and their community of practitioners in the academic community are limited to static methods focused on defining who is doing what and where. However, to answer the questions of why and how a system operates within complex systems-of-systems interrelationships, a system\u27s architecture and context must be observed over time, its executable architecture, to discern effective predictable and unpredictable behavior. The objective of this research is to determine a method for evaluating a system\u27s executable architecture and assess the contribution and efficiency of the specified system before it is built. This research led to the development of concrete steps that synthesize the observance of the executable architecture, assessment recommendations provided by the North Atlantic Treaty Organization (NATO) Code of Best Practice for Command and Control (C2) Assessment, and the metrics for operational efficiency provided by the Military Missions and Means Framework. Based on the research herein, this synthesis is designed to evaluate and assess system-of-systems architectures in their operational context to provide quantitative results

Report from GI-Dagstuhl Seminar 16394: Software Performance Engineering in the DevOps World

This report documents the program and the outcomes of GI-Dagstuhl Seminar 16394 "Software Performance Engineering in the DevOps World". The seminar addressed the problem of performance-aware DevOps. Both, DevOps and performance engineering have been growing trends over the past one to two years, in no small part due to the rise in importance of identifying performance anomalies in the operations (Ops) of cloud and big data systems and feeding these back to the development (Dev). However, so far, the research community has treated software engineering, performance engineering, and cloud computing mostly as individual research areas. We aimed to identify cross-community collaboration, and to set the path for long-lasting collaborations towards performance-aware DevOps. The main goal of the seminar was to bring together young researchers (PhD students in a later stage of their PhD, as well as PostDocs or Junior Professors) in the areas of (i) software engineering, (ii) performance engineering, and (iii) cloud computing and big data to present their current research projects, to exchange experience and expertise, to discuss research challenges, and to develop ideas for future collaborations

Simulation Software as a Service and Service-Oriented Simulation Experiment

Simulation software is being increasingly used in various domains for system analysis and/or behavior prediction. Traditionally, researchers and field experts need to have access to the computers that host the simulation software to do simulation experiments. With recent advances in cloud computing and Software as a Service (SaaS), a new paradigm is emerging where simulation software is used as services that are composed with others and dynamically influence each other for service-oriented simulation experiment on the Internet. The new service-oriented paradigm brings new research challenges in composing multiple simulation services in a meaningful and correct way for simulation experiments. To systematically support simulation software as a service (SimSaaS) and service-oriented simulation experiment, we propose a layered framework that includes five layers: an infrastructure layer, a simulation execution engine layer, a simulation service layer, a simulation experiment layer and finally a graphical user interface layer. Within this layered framework, we provide a specification for both simulation experiment and the involved individual simulation services. Such a formal specification is useful in order to support systematic compositions of simulation services as well as automatic deployment of composed services for carrying out simulation experiments. Built on this specification, we identify the issue of mismatch of time granularity and event granularity in composing simulation services at the pragmatic level, and develop four types of granularity handling agents to be associated with the couplings between services. The ultimate goal is to achieve standard and automated approaches for simulation service composition in the emerging service-oriented computing environment. Finally, to achieve more efficient service-oriented simulation, we develop a profile-based partitioning method that exploits a system’s dynamic behavior and uses it as a profile to guide the spatial partitioning for more efficient parallel simulation. We develop the work in this dissertation within the application context of wildfire spread simulation, and demonstrate the effectiveness of our work based on this application

Review of Open Source Simulators in ICS/IIoT Security Context

In industrial control systems (ICS), simulation has found widespread use during system design and in tuning process control parameters or exploring the effects of new control algorithms. Simulation enables the assessment of performance at scale and allows research to be conducted by those with limited access to real physical infrastructures. However, as ICSs are often no longer isolated from other networks and the internet, hence are subject to security and safety issues, simulation is also required to understand the issues and their solution. To foster transparent, collaborative and cost-effective studies, demonstrations, and solution development, and attract the broadest interest base, simulation is indeed critical and Open Source is a good way to go since simulators in this category are less expensive to access, install, and use, and can be run with general purpose (non-proprietary) computing equipment and setups. Findings This research presents the following key findings: 1. A lot of Open Source simulation tools exist and span applications areas such as communications and sensor networks (C&WSNs), ICS/SCADA, and IIoT. 2. The functional structures and characteristics that appear common in Open Source simulators include: supported licence types, programming languages, operating systems platforms, user interface types, and available documentation and types. 3. Typical research around Open Source simulators is built around modelling, analysis and optimisation of operations in relations to factors such as flexibility, mobility, scalability, and active user support. No single Open Source simulator addresses all conceivable characteristics. While some are strong in specific contexts relative to their development, they are often weak in other purpose-based research capabilities, especially in the context of IoT. 4. Most of the reviewed Open Source tools are not designed to address security contexts. The few that address security such as SCADASim only consider very limited contexts such as testing and evaluating Denial-of-Service (DoS), Man-in-the-middle (Mitm), Eavesdropping, and Spoofing attacks. Recommendations The following key recommendations are presented: 1. Future developments of Open Source simulators (especially for IIoT) should explore the potential for functionalities that can enable the integration of diverse simulators and platforms to achieve an encompassing setup. 2. Developers should explore the capabilities of generic simulators towards achieving architectures with expansible capabilities into multi-class domains, support easier and faster modelling of complex systems, and which can attract varied users and contributors. 3. Functional characteristics such as; ease of use, degree of community acceptance and use, and suitability for industrial applications, should also be considered as selection and development criteria, and to emphasise simulator effectiveness. This can support consistency, credibility, and simulation system relevance within a domain that is continually evolving. 4. Future Open Source simulation projects developments should consider and adopt the more common structural attributes including; Platform Type, Open Source Licence Type, Programming Language, User Interfaces, Documentation, and Communication Types. These should be further complemented by appropriate editorial controls spanning quality coding, revision control and effective project disseminations and management, to boost simulation tool credibility and wide acceptance. 5. The range of publication dates (earliest to latest) for: citations, code commits, and number of contributors associated to Open Source simulator projects can also support the decision for interests and adoption of specific Open Source projects. 6. Research objectives for ICS/IIoT Open Source simulators should also include security performance and optimisation with considerations towards enhancing confidentiality, integrity and availability. 7. Further studies should explore the evaluation of security topics which could be addressed by simulation – more specifically, proposing how this may be achieved and identifying what can't be addressed by simulation. Investigations into simulation frameworks that can allow multi-mode simulations to be configured and operated are also required. Research into Industry 4.0 System-of-Systems (SoS) security evaluations, dependency, and cascading impacts method or analysis is another area of importanc

A Three-Year Focused Initiative to Reduce Maternal Distress for Better Child Outcomes

During pregnancy and the first two years of parenting (i.e. the perinatal period) maternal distress (trauma, depression, and/or stress) can create an environment for the developing fetus and, later, for the very young child that will have negative developmental and educational impacts over the course of the child's life.  Too many children are born into isolated, vulnerable families where these multiple stressors give rise to an inhospitable environment for the critical first years of development.For the past decade, especially with advances in understanding brain development and its connections to lifecycle outcomes in development and health, research has increasingly focused on the role of stress in childhood morbidity and mortality.  Evidence is mounting that stress in pregnancy may be a significant factor contributing to negative birth outcomes (e.g. premature birth and low birth weight).The effects of maternal distress in pregnancy are frequently reinforced and potentially worsened by an environment of "toxic stress" for a baby or young child.  Toxic stress can change the expression of certain traits over the life course of an individual, potentially accounting for the higher rates of diabetes, obesity, and developmental delays seen in many children living in poverty

Hybrid Multiresolution Simulation & Model Checking: Network-On-Chip Systems

abstract: Designers employ a variety of modeling theories and methodologies to create functional models of discrete network systems. These dynamical models are evaluated using verification and validation techniques throughout incremental design stages. Models created for these systems should directly represent their growing complexity with respect to composition and heterogeneity. Similar to software engineering practices, incremental model design is required for complex system design. As a result, models at early increments are significantly simpler relative to real systems. While experimenting (verification or validation) on models at early increments are computationally less demanding, the results of these experiments are less trustworthy and less rewarding. At any increment of design, a set of tools and technique are required for controlling the complexity of models and experimentation. A complex system such as Network-on-Chip (NoC) may benefit from incremental design stages. Current design methods for NoC rely on multiple models developed using various modeling frameworks. It is useful to develop frameworks that can formalize the relationships among these models. Fine-grain models are derived using their coarse-grain counterparts. Moreover, validation and verification capability at various design stages enabled through disciplined model conversion is very beneficial. In this research, Multiresolution Modeling (MRM) is used for system level design of NoC. MRM aids in creating a family of models at different levels of scale and complexity with well-formed relationships. In addition, a variant of the Discrete Event System Specification (DEVS) formalism is proposed which supports model checking. Hierarchical models of Network-on-Chip components may be created at different resolutions while each model can be validated using discrete-event simulation and verified via state exploration. System property expressions are defined in the DEVS language and developed as Transducers which can be applied seamlessly for model checking and simulation purposes. Multiresolution Modeling with verification and validation capabilities of this framework complement one another. MRM manages the scale and complexity of models which in turn can reduces V&V time and effort and conversely the V&V helps ensure correctness of models at multiple resolutions. This framework is realized through extending the DEVS-Suite simulator and its applicability demonstrated for exemplar NoC models.Dissertation/ThesisDoctoral Dissertation Computer Science 201

A review of wildland fire spread modelling, 1990-present 3: Mathematical analogues and simulation models

In recent years, advances in computational power and spatial data analysis (GIS, remote sensing, etc) have led to an increase in attempts to model the spread and behvaiour of wildland fires across the landscape. This series of review papers endeavours to critically and comprehensively review all types of surface fire spread models developed since 1990. This paper reviews models of a simulation or mathematical analogue nature. Most simulation models are implementations of existing empirical or quasi-empirical models and their primary function is to convert these generally one dimensional models to two dimensions and then propagate a fire perimeter across a modelled landscape. Mathematical analogue models are those that are based on some mathematical conceit (rather than a physical representation of fire spread) that coincidentally simulates the spread of fire. Other papers in the series review models of an physical or quasi-physical nature and empirical or quasi-empirical nature. Many models are extensions or refinements of models developed before 1990. Where this is the case, these models are also discussed but much less comprehensively.Comment: 20 pages + 9 pages references + 1 page figures. Submitted to the International Journal of Wildland Fir

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

Understanding the Elements of Executable Architectures Through a Multi-Dimensional Analysis Framework

The objective of this dissertation study is to conduct a holistic investigation into the elements of executable architectures. Current research in the field of Executable Architectures has provided valuable solution-specific demonstrations and has also shown the value derived from such an endeavor. However, a common theory underlying their applications has been missing. This dissertation develops and explores a method for holistically developing an Executable Architecture Specification (EAS), i.e., a meta-model containing both semantic and syntactic information, using a conceptual framework for guiding data coding, analysis, and validation. Utilization of this method resulted in the description of the elements of executable architecture in terms of a set of nine information interrogatives: an executable architecture information ontology. Once the detail-rich EAS was constructed with this ontology, it became possible to define the potential elements of executable architecture through an intermediate level meta-model. The intermediate level meta-model was further refined into an interrogative level meta-model using only the nine information interrogatives, at a very high level of abstraction

Applying the levels of conceptual interoperability model in support of integratability, interoperability, and composability for system-of-systems engineering

The Levels of Conceptual Interoperability Model (LCIM) was developed to cope with the different layers of interoperation of modeling & simulation applications. It introduced technical, syntactic, semantic, pragmatic, dynamic, and conceptual layers of interoperation and showed how they are related to the ideas of integratability, interoperability, and composability. The model was successfully applied in various domains of systems, cybernetics, and informatics