This paper describes the use of the Levels of Conceptual Interoperability Model (LCIM) as a framework for conceptual modeling and its descriptive and prescriptive uses. LCIM is applied to show its potential and shortcomings in the current simulation interoperability approaches, in particular the High Level Architecture (HLA) and Base Object Models (BOM). It emphasizes the need to apply rigorous engineering methods and principles and replace ad-hoc approaches.
Building meaningful interoperation with external software units requires performing the conceptual interoperability analysis that starts with identifying the conceptual interoperability constraints of each software unit, then it compares the systems' constraints to detect their conceptual mismatch. We call the conceptual interoperability constraints (the COINs) that can be of different types including structure, dynamic, and quality. Missing such constraints may lead to unexpected mismatches, expensive resolution, and running-late projects. However, it is a challenging task for software archit…
By introducing a common representational system for metadata that describe the employed simulation workflows, diverse sources of data and platforms in computational molecular engineering, such as workflow management systems, can become interoperable at the semantic level. To achieve semantic interoperability, the present work introduces two ontologies that provide a formal specification of the entities occurring in a simulation workflow and the relations between them: The software ontology VISO is developed to represent software packages and their features, and OSMO, an ontology for simulation…
Models are fundamentally crucial to many scientific fields, including software engineering, systems engineering, enterprise modeling, and business modeling. This paper focuses on diagrammatic conceptual modeling, as opposed to mathematical or computational models, wherein a conceptual model is a translation of reality processes into an abstract mechanism that has similar structure and parallel events of the external processes. Although various modeling approaches exist, including UML (Unified Modeling Language) in software engineering and its dialect, SysML (System Modeling Language), in syste…
The Mediation Information System Engineering project is currently finishing its second iteration (MISE 2.0). The main objective of this scientific project is to provide any emerging collaborative situation with methods and tools to deploy a Mediation Information System (MIS). MISE 2.0 aims at defining and designing a service-based platform, dedicated to initiating and supporting the interoperability of collaborative situations among potential partners. This MISE 2.0 platform implements a model-driven engineering approach to the design of a service-oriented MIS dedicated to supporting the colla…
The increasing importance of such fields as embedded systems, pervasive computing, and hybrid systems control is increasing attention to the time-dependent aspects of system modeling. In this paper, we focus on modeling conceptual time. Conceptual time is time represented in conceptual modeling, where the notion of time does not always play a major role. Time modeling in computing is far from exhibiting a unified and comprehensive framework, and is often handled in an ad hoc manner. This paper contributes to the establishment of a broader understanding of time in conceptual modeling based on a…
Requirements engineering (RE), as a part of the project development life cycle, has increasingly been recognized as the key to ensuring on-time, on-budget, and goal-based delivery of software projects;compromising this vital phase is nothing but project failures. RE of big data projects is even more crucial because of the main characteristics of big data, including high volume, velocity, and variety. As the traditional RE methods and tools are user-centric rather than data-centric, employing these methodologies is insufficient to fulfill the RE processes for big data projects. Because of the i…
This paper studies the differences and similarities between domain ontologies and conceptual data models and the role that ontologies can play in establishing conceptual data models during the process of information systems development. A mapping algorithm has been proposed and embedded in a special purpose Transformation Engine to generate a conceptual data model from a given domain ontology. Both quantitative and qualitative methods have been adopted to critically evaluate this new approach. In addition, this paper focuses on evaluating the quality of the generated conceptual data model elem…
This paper aims to contribute to further understanding of dynamism (the dynamic behavior of system models) in the mathematical and conceptual modeling of systems. This study is conducted in the context of the claim that software engineering lacks underpinning scientific theories, both for the software it produces and the processes by which it does so. The research literature proposes that information theory can provide such a benefit for software engineering. We explore the dynamism expressive power of conceptual modeling as a software engineering tool that can represent physical systems in th…
The use of conceptual models to foster requirements engineering has been proposed and evaluated as beneficial for several decades. For instance, goal-oriented requirements engineering or the specification of scenarios are commonly done using conceptual models. Bringing such model-based requirements engineering approaches into industrial practice typically requires industrial training. In this paper, we report lessons learned from a training program for teaching industry professionals model-based requirements engineering. Particularly, we as educators and learners report experiences from design…
This paper has a dual character, combining a philosophical ontological exploration with a conceptual modeling approach in systems and software engineering. Such duality is already practiced in software engineering, in which the current dominant modeling thesis is object orientation. This work embraces an anti-thesis that centers solely on the process rather than emphasizing the object. The approach is called occurrence-only modeling, in which an occurrence means an event or process where a process is defined as an orchestrated net of events that form a semantical whole. In contrast to object o…
This paper is about conceptual modeling of aggregates in software engineering. An aggregate is a cluster of domain objects that can be treated as a single unit. In UML, an aggregation is a type of association in which objects are configured together to form a more complex object. It has been described as one of the biggest betes noires in modeling. In spite of its widespread use, aggregation seems a troublesome concept. It is sometimes treated as part-of; however, the part-of relation is only one of many possible aggregation mechanisms and is itself problematical, partly because of its diverse…
With recent advances in the development of more powerful quantum computers, the re-search area of quantum software engineering is emerging. Quantum software plays a critical role in exploiting the full potential of quantum computing systems. As a result, it has been drawing increasing attention recently to provide concepts, principles, and guidelines to address the ongoing challenges of quantum software development. The importance of the topic motivated us to voice out a call for action to develop a readiness model that will help an organization assess its capability of migration from classic …
Over recent decades, scenarios and scenario-based software/system engineering have been actively employed as essential tools to handle intricate problems, validate requirements, and support stakeholders' communication. However, despite the widespread use of scenarios, there have been several challenges for engineers to more willingly utilize scenario-based engineering approaches (i.e., scenario methods) in their projects. First, the term scenario has numerous published definitions, thus lacking in a well-established shared understanding of scenarios and scenario methods. Second, the conceptual…
This study introduces another application of software engineering tools, conceptual modeling, which can be applied to other fields of research. One way to strengthen the relationship between software engineering and other fields is to develop a good way to perform conceptual modeling that is capable of addressing the peculiarities of these fields of study. This study concentrates on humanities and social sciences, which are usually considered softer and further away from abstractions and (abstract) machines. Specifically, we focus on conceptual modeling as a software engineering tool (e.g., UM…
In previous works, we proposed a one-category (entitled thimac) conceptual model called a thinging machine (TM), which integrates staticity (e.g., objects) and dynamism (e.g., events) without losing valuable aspects of diagrammatic intuition in conceptual modeling. We proposed applying TM to conceptual modeling in software engineering (e.g., on or above the level of UML as a conceptual modeling language). In this paper, to show such an application in software engineering, we first present a complete high-level description of a library service system to demonstrate the TM s applicability. Furth…
In software engineering, conceptual modeling focuses on creating representations of the world that are as faithful and rich as possible, with the aim of guiding the development of software systems. In contrast, in the computing realm, the notion of ontology has been characterized as being closely related to conceptual modeling and is often viewed as a specification of a conceptualization. Accordingly, conceptual modeling and ontology engineering now address the same problem of representing the world in a suitable fashion. A high-level ontology provides a means to describe concepts and their in…
Abstraction applied in computer networking hides network details behind a well-defined representation by building a model that captures an essential aspect of the network system. Two current methods of representation are available, one based on graph theory, where a network node is reduced to a point in a graph, and the other the use of non-methodological iconic depictions such as human heads, walls, towers or computer racks. In this paper, we adopt an abstract representation methodology, the thinging machine (TM), proposed in software engineering to model computer networks. TM defines a singl…
The use of model such as LEL (Lexicon Extended Language) in natural language is very interesting in Requirements Engineering. But LEL, even if it is derived from the Universe of Discourse (UofD) does not provide further details on the concepts it describes. However, we believe that the elements inherent in the conceptual level of a system are already defined in the Universe of Discourse. Therefore, in this work we propose a more elaborate natural language model called eLEL. It is a model that describes the concepts in a domain in more detail than the conventional LEL. We also propose a modelin…
In this paper, we concentrate on object-related analysis in the field of general ontology of reality as related to software engineering (e.g., UML classes). Such a venture is similar to many studies in which researchers have enhanced modeling through ontological analysis of the underlying paradigm of UML models. We attempt to develop a conceptual model that consists of a foundation of things that is supplemented with a second level of designated objects. According to some researchers, the problem of the difference between things and objects is one of the most decisive issues for the conception…
Analytics corresponds to a relevant and challenging phase of Big Data. The generation of knowledge from extensive data sets (petabyte era) of varying types, occurring at a speed able to serve decision makers, is practiced using multiple areas of knowledge, such as computing, statistics, data mining, among others. In the Big Data domain, Analytics is also considered as a process capable of adding value to the organizations. Besides the demonstration of value, Analytics should also consider operational tools and models to support decision making. To adding value, Analytics is also presented as p…
A growing number of empirical software engineering researchers suggest that a complementary focus on theory is required if the discipline is to mature. A first step in theory-building involves the establishment of suitable theoretical constructs. For researchers studying software projects, the lack of a theoretical construct for context is problematic for both experimentation and effort estimation. For experiments, insufficiently understood contextual factors confound results, and for estimation, unstated contextual factors affect estimation reliability. We have earlier proposed a framework th…
An important factor in guaranteeing the quality of a system is developing a conceptual model that reflects the knowledge about its domain as well as knowledge about the functions it has to perform. In software engineering, conceptual modeling has gained importance as a discipline that offers languages, methods, and methodologies to address the complexity of software development. The key to understanding such complexity is using tools such as diagrams at various levels of representation. A conceptual model must include all relevant static and behavioral aspects of its domain. In UML, the static…
Engineering software for robotics applications requires multidomain and application-specific solutions. Model-driven engineering and modeling language integration provide means for developing specialized, yet reusable models of robotics software architectures. Code generators transform these platform independent models into executable code specific to robotic platforms. Generative software engineering for multidomain applications requires not only the integration of modeling languages but also the integration of validation mechanisms and code generators. In this paper we sketch a conceptual mo…
Researchers have been highly active to investigate the classical machine learning workflow and integrate best practices from the software engineering lifecycle. However, deep learning exhibits deviations that are not yet covered in this conceptual development process. This includes the requirement of dedicated hardware, dispensable feature engineering, extensive hyperparameter optimization, large-scale data management, and model compression to reduce size and inference latency. Individual problems of deep learning are under thorough examination, and numerous concepts and implementations have g…
This report describes de design of an experiment that intends to compare two variants of a modeldriven system development method, so as to assess the impact of requirements engineering practice in the quality of the conceptual models. The conceptual modelling method being assessed is the OO-Method [Pastor and Molina 2007]. One of its variants includes Communication Analysis, a communication-oriented requirements engineering method [España, González et al. 2009] and a set of guidelines to derive conceptual models from requirements models [España, Ruiz et al. 2011; González, España et al. 2011].…
Following established tradition, software engineering today is rooted in a conceptually centralized way of thinking. The primary SE artifact is a specification of a machine -- a computational artifact -- that would meet the (elicited and) stated requirements. Therein lies a fundamental mismatch with (open) sociotechnical systems, which involve multiple autonomous social participants or principals who interact with each other to further their individual goals. No central machine governs the behaviors of the various principals. We introduce Interaction-Oriented Software Engineering (IOSE) as an …
