1,889 research outputs found
Semantics of trace relations in requirements models for consistency checking and inferencing
Requirements traceability is the ability to relate requirements back to stakeholders and forward to corresponding design artifacts, code, and test cases. Although considerable research has been devoted to relating requirements in both forward and backward directions, less attention has been paid to relating requirements with other requirements. Relations between requirements influence a number of activities during software development such as consistency checking and change management. In most approaches and tools, there is a lack of precise definition of requirements relations. In this respect, deficient results may be produced. In this paper, we aim at formal definitions of the relation types in order to enable reasoning about requirements relations. We give a requirements metamodel with commonly used relation types. The semantics of the relations is provided with a formalization in first-order logic. We use the formalization for consistency checking of relations and for inferring new relations. A tool has been built to support both reasoning activities. We illustrate our approach in an example which shows that the formal semantics of relation types enables new relations to be inferred and contradicting relations in requirements documents to be determined. The application of requirements reasoning based on formal semantics resolves many of the deficiencies observed in other approaches. Our tool supports better understanding of dependencies between requirements
Generating collaborative systems for digital libraries: A model-driven approach
This is an open access article shared under a Creative Commons Attribution 3.0 Licence (http://creativecommons.org/licenses/by/3.0/). Copyright @ 2010 The Authors.The design and development of a digital library involves different stakeholders, such as: information architects, librarians, and domain experts, who need to agree on a common language to describe, discuss, and negotiate the services the library has to offer. To this end, high-level, language-neutral models have to be devised. Metamodeling techniques favor the definition of domainspecific visual languages through which stakeholders can share their views and directly manipulate representations of the domain entities. This paper describes CRADLE (Cooperative-Relational Approach to Digital Library Environments), a metamodel-based framework and visual language for the definition of notions and services related to the development of digital libraries. A collection of tools allows the automatic generation of several services, defined with the CRADLE visual language, and of the graphical user interfaces providing access to them for the final user. The effectiveness of the approach is illustrated by presenting digital libraries generated with CRADLE, while the CRADLE environment has been evaluated by using the cognitive dimensions framework
Enriching Linked Data with Semantics from Domain-Specific Diagrammatic Models
One key driver of the Linked Data paradigm is the ability to lift data graphs from legacy systems by employing various adapters and RDFizers (e.g., D2RQ for relational databases, XLWrap for spreadsheets). Such approaches aim towards removing boundaries of enterprise data silos by opening them to cross-organizational linking within a âWeb of Dataâ. An insufficiently tapped source of machine-readable semantics is the underlying graph nature of diagrammatic conceptual models â a kind of information that is richer compared to what is typically lifted from table schemata, especially when a domain-specific modeling language is employed. The paper advocates an approach to Linked Data enrichment based on a diagrammatic model RDFizer originally developed in the context of the ComVantage FP7 research project. A minimal but illustrative example is provided from which arguments will be generalized, leading to a proposed vision of âconceptual modelâ-aware information systems
A Metamodeling Approach to Teaching Conceptual Modeling at Large
In the authors\u27 university there is a challenge, with respect to Conceptual Modeling topics, of bridging the gap between bachelor-level studies and research work. At bachelor-level, Conceptual Modeling is subordinated to Software Engineering topics consequently making extensive use of software design standards. However, at doctoral level or in project-based work, modeling methods must be scientifically framed within wider-scoped paradigms - Design Science, Enterprise Modeling etc. In order to bridge this gap, we developed a teaching artifact to present Conceptual Modeling as a standalone discipline that can produce its own artifacts, driven by requirements in a variety of domains. The teaching artifact is an agile modeling method that is iteratively implemented by students. The key takeaway revelation for students is that a modeling language is a knowledge schema that can be tailored and migrated for specific purposes just like a database schema, to accommodate an application domain and its modeling requirements
Change Impact Analysis based on Formalization of Trace Relations for Requirements
Evolving customer needs is one of the driving factors in software development. There is a need to analyze the impact of requirement changes in order to determine possible conflicts and design alternatives influenced by these changes. The analysis of the impact of requirement changes on related requirements can be based on requirements traceability. In this paper, we propose a requirements metamodel with well defined types of requirements relations. This metamodel represents the common concepts extracted from some prevalent requirements engineering approaches. The requirements relations in the metamodel are used to trace related requirements for change impact analysis. We formalize the relations. Based on this formalization, we define change impact rules for requirements. As a case study, we apply these rules to changes in the requirements specification for Course Management System
A Process Model for Component-Based Model-Driven Software Development
Developing high quality, reliable and on time software systems is challenging due to the increasing size and complexity of these systems. Traditional software development approaches are not
suitable for dealing with such challenges, so several approaches have been introduced to increase the productivity and reusability during the software development process. Two of these approaches are
Component-Based Software Engineering (CBSE) and Model-Driven Software Development (MDD) which focus on reusing pre-developed code and using models throughout the development process
respectively. There are many research studies that show the benefits of using software components and model-driven approaches. However, in many cases the development process is either ad-hoc or
not well-defined. This paper proposes a new software development process model that merges CBSE and MDD principles to facilitate software development. The model is successfully tested by applying
it to the development of an e-learning system as an exemplar case stud
An Open Platform for Modeling Method Conceptualization: The OMiLAB Digital Ecosystem
This paper motivates, describes, demonstrates in use, and evaluates the Open Models Laboratory (OMiLAB)âan open digital ecosystem designed to help one conceptualize and operationalize conceptual modeling methods. The OMiLAB ecosystem, which a generalized understanding of âmodel valueâ motivates, targets research and education stakeholders who fulfill various roles in a modeling method\u27s lifecycle. While we have many reports on novel modeling methods and tools for various domains, we lack knowledge on conceptualizing such methods via a full-fledged dedicated open ecosystem and a methodology that facilitates entry points for novices and an open innovation space for experienced stakeholders. This gap continues due to the lack of an open process and platform for 1) conducting research in the field of modeling method design, 2) developing agile modeling tools and model-driven digital products, and 3) experimenting with and disseminating such methods and related prototypes. OMiLAB incorporates principles, practices, procedures, tools, and services required to address the issues above since it focuses on being the operational deployment for a conceptualization and operationalization process built on several pillars: 1) a granularly defined âmodeling methodâ concept whose building blocks one can customize for the domain of choice, 2) an âagile modeling method engineeringâ framework that helps one quickly prototype modeling tools, 3) a model-aware âdigital product design labâ, and 4) dissemination channels for reaching a global community. In this paper, we demonstrate and evaluate the OMiLAB in research with two selected application cases for domain- and case-specific requirements. Besides these exemplary cases, OMiLAB has proven to effectively satisfy requirements that almost 50 modeling methods raise and, thus, to support researchers in designing novel modeling methods, developing tools, and disseminating outcomes. We also measured OMiLABâs educational impact
Analytical metadata modeling for next generation BI systems
Business Intelligence (BI) systems are extensively used as in-house solutions to support decision-making in organizations. Next generation BI 2.0 systems claim for expanding the use of BI solutions to external data sources and assisting the user in conducting data analysis. In this context, the Analytical Metadata (AM) framework defines the metadata artifacts (e.g., schema and queries) that are exploited for user assistance purposes. As such artifacts are typically handled in ad-hoc and system specific manners, BI 2.0 argues for a flexible solution supporting metadata exploration across different systems.
In this paper, we focus on the AM modeling. We propose SM4AM, an RDF-based Semantic Metamodel for AM. On the one hand, we claim for ontological metamodeling as the proper solution, instead of a fixed universal model, due to (meta)data models heterogeneity in BI 2.0. On the other hand, RDF provides means for facilitating defining and sharing flexible metadata representations. Furthermore, we provide a method to instantiate our metamodel. Finally, we present a real-world case study and discuss how SM4AM, specially the schema and query artifacts, can help traversing different models instantiating our metamodel and enabling innovative means to explore external repositories in what we call metamodel-driven (meta)data exploration.Peer ReviewedPostprint (author's final draft
- âŠ