A taxonomy of asymmetric requirements aspects

The early aspects community has received increasing attention among researchers and practitioners, and has grown a set of meaningful terminology and concepts in recent years, including the notion of requirements aspects. Aspects at the requirements level present stakeholder concerns that crosscut the problem domain, with the potential for a broad impact on questions of scoping, prioritization, and architectural design. Although many existing requirements engineering approaches advocate and advertise an integral support of early aspects analysis, one challenge is that the notion of a requirements aspect is not yet well established to efficaciously serve the community. Instead of defining the term once and for all in a normally arduous and unproductive conceptual unification stage, we present a preliminary taxonomy based on the literature survey to show the different features of an asymmetric requirements aspect. Existing approaches that handle requirements aspects are compared and classified according to the proposed taxonomy. In addition,we study crosscutting security requirements to exemplify the taxonomy's use, substantiate its value, and explore its future directions

Using real options to select stable Middleware-induced software architectures

The requirements that force decisions towards building distributed system architectures are usually of a non-functional nature. Scalability, openness, heterogeneity, and fault-tolerance are examples of such non-functional requirements. The current trend is to build distributed systems with middleware, which provide the application developer with primitives for managing the complexity of distribution, system resources, and for realising many of the non-functional requirements. As non-functional requirements evolve, the `coupling' between the middleware and architecture becomes the focal point for understanding the stability of the distributed software system architecture in the face of change. It is hypothesised that the choice of a stable distributed software architecture depends on the choice of the underlying middleware and its flexibility in responding to future changes in non-functional requirements. Drawing on a case study that adequately represents a medium-size component-based distributed architecture, it is reported how a likely future change in scalability could impact the architectural structure of two versions, each induced with a distinct middleware: one with CORBA and the other with J2EE. An option-based model is derived to value the flexibility of the induced-architectures and to guide the selection. The hypothesis is verified to be true for the given change. The paper concludes with some observations that could stimulate future research in the area of relating requirements to software architectures

A Comprehensive Study for Modern Models: Linking Requirements with Software Architectures

Several models recently have been addressed in software engineering for requirements transformation. However, such transformation models have encountered many problems due to the nature of requirements. In the classical transformation modeling, some requirements are discovered to be missing or erroneous at later stages, in addition to major assumptions that may affect the quality of the software. This has created a crucial need for new approaches to requirements transformation. In this paper, a comprehensive study is presented in the main modern models of linking requirements to software architectures. An extensive evaluation is conducted to investigate the capabilities of such modern models to overcome those limitations when transforming requirements, validating their consideration of bringing quality for the software development process. Key research gaps and open issues are discussed, highlighting the possible future directions that can be considered in this field

Analysis of Existing Approaches to Constructing Component-based Systems Directly from Natural Language Requirements

System development generally starts with Requirements Engineering (RE) process. Based on requirements, system analysts produce the requirements documents and analyze them in order to produce design documents. These artefacts will be inputs to the later stages in the system development. It is argued that during the transition between these stages, considering many other various factors, information might be missed out or misinterpreted along the way. Hence, a better transition in the development cycle is required. This paper outlines and provides an analysis of the existing approaches in the literature on constructing systems from natural language requirements (NLR) as to provide the motivation of a new approach to constructing component-based system from NLR

Interplay of Security&Dependability and Resource using Model-driven and Pattern-based Development

International audienceSeveral frameworks have been proposed to help designers of embedded system applications. However, we currently lack methodological tool support to take into account the interplay between security&;dependability and resource properties. In this work, we propose a modeling environment which associates model-driven paradigms with security and dependability patterns to ensure that the combination of security and dependability solutions fit on the targeted hardware platform. The resulted framework will serve as a tool to estimate the resources consumed by the security and dependability solutions at early stages of design to help the designer to avoid resource conflicts at run-time. In addition, we provide an architecture for development tools to support the design and the analysis of pattern-based secure and dependable applications. Finally, we apply it in practice to a use case from railway domain with strong security and dependability requirements

Sensemaking Practices in the Everyday Work of AI/ML Software Engineering

This paper considers sensemaking as it relates to everyday software engineering (SE) work practices and draws on a multi-year ethnographic study of SE projects at a large, global technology company building digital services infused with artificial intelligence (AI) and machine learning (ML) capabilities. Our findings highlight the breadth of sensemaking practices in AI/ML projects, noting developers' efforts to make sense of AI/ML environments (e.g., algorithms/methods and libraries), of AI/ML model ecosystems (e.g., pre-trained models and "upstream"models), and of business-AI relations (e.g., how the AI/ML service relates to the domain context and business problem at hand). This paper builds on recent scholarship drawing attention to the integral role of sensemaking in everyday SE practices by empirically investigating how and in what ways AI/ML projects present software teams with emergent sensemaking requirements and opportunities

A Compositional Approach to Creating Architecture Frameworks with an Application to Distributed AI Systems

Artificial intelligence (AI) in its various forms finds more and more its way into complex distributed systems. For instance, it is used locally, as part of a sensor system, on the edge for low-latency high-performance inference, or in the cloud, e.g. for data mining. Modern complex systems, such as connected vehicles, are often part of an Internet of Things (IoT). To manage complexity, architectures are described with architecture frameworks, which are composed of a number of architectural views connected through correspondence rules. Despite some attempts, the definition of a mathematical foundation for architecture frameworks that are suitable for the development of distributed AI systems still requires investigation and study. In this paper, we propose to extend the state of the art on architecture framework by providing a mathematical model for system architectures, which is scalable and supports co-evolution of different aspects for example of an AI system. Based on Design Science Research, this study starts by identifying the challenges with architectural frameworks. Then, we derive from the identified challenges four rules and we formulate them by exploiting concepts from category theory. We show how compositional thinking can provide rules for the creation and management of architectural frameworks for complex systems, for example distributed systems with AI. The aim of the paper is not to provide viewpoints or architecture models specific to AI systems, but instead to provide guidelines based on a mathematical formulation on how a consistent framework can be built up with existing, or newly created, viewpoints. To put in practice and test the approach, the identified and formulated rules are applied to derive an architectural framework for the EU Horizon 2020 project ``Very efficient deep learning in the IoT" (VEDLIoT) in the form of a case study