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

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

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

REPRESENTATION AND REASONING MODELS FOR C3 ARCHITECTURE DESCRIPTION LANGUAGE

International audienceComponent-based development is a proven approach to manage the complexity of software and its need for customization. At an architectural level, one describes the principal system components and their pathways of interaction. So, Architecture is considered to be the driving aspect of the development process; it allows specifying which aspects and models in each level needed according to the software architecture design. Early Architecture description languages (ADLs), nearly exclusive, focus on structural abstraction hierarchy ignoring behavioural description hierarchy, conceptual hierarchy, and metamodeling hierarchy. In this paper we focus on those four hierarchies which represent views to appropriately “reason about” software architectures described using our C3 metamodel which is a minimal and complete architecture description language. In this paper we provide a set of mechanisms to deal with different levels of each hierarchy, also we introduce our proper structural definition for connector's elements deployed in C3 Architectures

Ontologies in domain specific languages : a systematic literature review

The systematic literature review conducted in this paper explores the current techniques employed to leverage the development of DSLs using ontologies. Similarities and differences between ontologies and DSLs, techniques to combine DSLs with ontologies, the rationale of these techniques and challenges in the DSL approaches addressed by the used techniques have been investigated. Details about these topics have been provided for each relevant research paper that we were able to investigate in the limited amount of time of one month. At the same time, a synthesis describing the main trends in all the topics mentioned above has been done

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 “Web of Data”. An insufficiently tapped source of machine-readable semantics is the underlying graph nature of diagrammatic conceptual models – 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 “conceptual model”-aware information systems

A Proposal for Deploying Hybrid Knowledge Bases: the ADOxx-to-GraphDB Interoperability Case

Graph Database Management Systems brought data model abstractions closer to how humans are used to handle knowledge - i.e., driven by inferences across complex relationship networks rather than by encapsulating tuples under rigid schemata. Another discipline that commonly employs graph-like structures is diagrammatic Conceptual Modeling, where intuitive, graphical means of explicating knowledge are systematically studied and formalized. Considering the common ground of graph databases, the paper proposes an integration of OWL ontologies with diagrammatic representations as enabled by the ADOxx metamodeling platform. The proposal is based on the RDF-semantics variant of OWL and leads to a particular type of hybrid knowledge bases hosted, for proof-of-concept purposes, by the GraphDB system due to its inferencing capabilities. The approach aims for complementarity and integration, providing agile diagrammatic means of creating semantic networks that are amenable to ontology-based reasoning