Crosscutting, what is and what is not? A Formal definition based on a Crosscutting Pattern

Crosscutting is usually described in terms of scattering and tangling. However, the distinction between these concepts is vague, which could lead to ambiguous statements. Sometimes, precise definitions are required, e.g. for the formal identification of crosscutting concerns. We propose a conceptual framework for formalizing these concepts based on a crosscutting pattern that shows the mapping between elements at two levels, e.g. concerns and representations of concerns. The definitions of the concepts are formalized in terms of linear algebra, and visualized with matrices and matrix operations. In this way, crosscutting can be clearly distinguished from scattering and tangling. Using linear algebra, we demonstrate that our definition generalizes other definitions of crosscutting as described by Masuhara & Kiczales [21] and Tonella and Ceccato [28]. The framework can be applied across several refinement levels assuring traceability of crosscutting concerns. Usability of the framework is illustrated by means of applying it to several areas such as change impact analysis, identification of crosscutting at early phases of software development and in the area of model driven software development

An XML-Based Approach to Handling Tables in Documents

We explore application of XML technology for handling tables in legacy semi-structured documents. Specifically, we analyze annotating heterogeneous documents containing tables to obtain a formalized XML Master document that improves traceability (hence easing verification and update) and enables manipulation using XSLT stylesheets. This approach is useful when table instances far outnumber distinct table types because the effort required to annotate a table instance is relatively less compared to formalizing table processing that respects table’s semantics. This work is also relevant for authoring new documents with tables that should be accessible to both humans and machines

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

PLiMoS, a DSML to Reify Semantics Relationships: An Application to Model-Based Product Lines

In the Model-Based Product Line Engineering (MBPLE) context, modularization and separation of concerns have been introduced to master the inherent complexity of current developments. With the aim to exploit e ciently the variabilities and commonalities in MBPLs, the challenge of management of dependencies becomes essential (e.g. hierarchical and variability decomposition, inter-dependencies between models). However, one may observe that, in existing approaches, relational information (i) is mixed with other concerns, and (ii) lacks semantics and abstraction level identi cation. To tackle this issue, we make explicit the relationships and their semantics, and separate the relational concern into a Domain Speci c Modeling Language (DSML) called PLiMoS. Relationships are treated as rst-class entities and quali ed by operational semantics properties, organized into viewpoints to address distinct objectives, e.g. product derivation, variability consistency management, archi- tectural organization. This paper provides a description of the PLiMoS relationships de nition and its implementation in a model-based product line process using two variability languages: Feature Model and OVM. The independence with variability and core assets modeling languages provides bene ts to cope with the product line maintenance

A Model-driven Approach for the Description of Blockchain Business Networks

The concept of blockchain technology has gained significant momentum in practice and research in the past few years, as it provides an effective way for addressing the issues of anonymity and traceability in distributed scenarios with multiple parties, which have to exchange information and want to securely collaborate with each other. However, up-to-date, the impact of the structure and setup of business networks on successfully applying blockchain technology, remains largely unexplored. We propose a model-driven approach, combining an ontology and a layer model, that is capable of capturing the properties of existing blockchain-driven business networks. The layers are used to facilitate the comprehensive description of such networks. We also introduce the Blockchain Business Network Ontology (BBO), formalizing the concepts and properties for describing the integral parts of a blockchain network. We show the practical applicability of our work by evaluating and applying it to an available blockchain use case

“Why can’t I do that?”: tracing adaptive security decisions

One of the challenges of any adaptive system is to ensure that users can understand how and why the behaviour of the system changes at runtime. This is particularly important for adaptive security behaviours which are essential for applications that are used in many different contexts, such as those hosted in the cloud. In this paper, we propose an approach for using traceability information, enriched with causality relations and contextual attributes of the deployment environment, when providing feedback to the users. We demonstrate, using a cloud storage-as-a-service environment, how our approach provides users of cloud applications better information, explanations and assurances about the security decisions made by the system. This enables the user to understand why a certain security adaptation has occurred, how the adaptation is related to current context of use of the application, and a guarantee that the application still satisfies its security requirements after an adaptation