Impact and Challenges of Software in 2025: Collected Papers

Today (2014), software is the key ingredient of most products and services. Software generates innovation and progress in many modern industries. Software is an indispensable element of evolution, of quality of life, and of our future. Software development is (slowly) evolving from a craft to an industrial discipline. Software – and the ability to efficiently produce and evolve high-quality software – is the single most important success factor for many highly competitive industries. Software technology, development methods and tools, and applications in more and more areas are rapidly evolving. The impact of software in 2025 in nearly all areas of life, work, relationships, culture, and society is expected to be massive. The question of the future of software is therefore important. However – like all predictions – quite difficult. Some market forces, industrial developments, social needs, and technology trends are visible today. How will they develop and influence the software we will have in 2025?:Impact of Heterogeneous Processor Architectures and Adaptation Technologies on the Software of 2025 (Kay Bierzynski) 9 Facing Future Software Engineering Challenges by Means of Software Product Lines (David Gollasch) 19 Capabilities of Digital Search and Impact on Work and Life in 2025 (Christina Korger) 27 Transparent Components for Software Systems (Paul Peschel) 37 Functionality, Threats and Influence of Ubiquitous Personal Assistants with Regard to the Society (Jonas Rausch) 47 Evolution-driven Changes of Non-Functional Requirements and Their Architecture (Hendrik Schön) 5

Reaction kinetics in formulated industrial catalysts

In heterogeneous catalysis, a fundamental understanding of the necessary physico-chemical requirements for a catalyst formulation is essential to its success. Understanding of reaction kinetics via modelling can demonstrate how catalysts work, providing functional information around surface active sites and reaction mechanism. This tool, combined with well-designed laboratory experiments to test a catalyst under steady and/or non-steady state conditions, can provide insight into the links between catalyst formulation and reaction performance. The aim of this project is to develop novel strategies and methods in these areas utilising a range of Johnson Matthey catalysts and reaction systems. This thesis places significant focus on obtaining mechanistically and statistically sound kinetic models with reliable model parameter estimates. Methods for this are developed using a batch liquid phase hydrogenation system using a Pt/TiO2 catalyst. Subsequently, non-steady state analysis of catalyst formulations has been explored. This includes the initial transient behaviour of a fresh vanadium phosphorus oxide selective oxidation catalyst under reaction conditions which allowed understanding of the evolution of distinct active site populations on the catalyst surface. A subsequent study of copper-based methanol synthesis catalysts explored the impact of gas phase conditions on the catalyst state. A mixture of steady-state testing and transient response experiments (i.e. via an imposed change in gas phase conditions over the catalyst) provided new insights into the evolution of active site populations and populations of surface species on the catalyst surface. Overall, the reaction kinetics studies demonstrated across this thesis demonstrate not only a series of methods to understand catalyst behaviour in depth but also to understand the key functional requirements for an effective industrial catalyst

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

Some Findings Concerning Requirements in Agile Methodologies

gile methods have appeared as an attractive alternative to conventional methodologies. These methods try to reduce the time to market and, indirectly, the cost of the product through flexible development and deep customer involvement. The processes related to requirements have been extensively studied in literature, in most cases in the frame of conventional methods. However, conclusions of conventional methodologies could not be necessarily valid for Agile; in some issues, conventional and Agile processes are radically different. As recent surveys report, inadequate project requirements is one of the most conflictive issues in agile approaches and better understanding about this is needed. This paper describes some findings concerning requirements activities in a project developed under an agile methodology. The project intended to evolve an existing product and, therefore, some background information was available. The major difficulties encountered were related to non-functional needs and management of requirements dependencies

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

Software Sustainability: The Modern Tower of Babel

<p>The aim of this paper is to explore the emerging definitions of software sustainability from the field of software engineering in order to contribute to the question, what is software sustainability?</p

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

Functional adaptivity for digital library services in e-infrastructures: the gCube approach

We consider the problem of e-Infrastructures that wish to reconcile the generality of their services with the bespoke requirements of diverse user communities. We motivate the requirement of functional adaptivity in the context of gCube, a service-based system that integrates Grid and Digital Library technologies to deploy, operate, and monitor Virtual Research Environments defined over infrastructural resources. We argue that adaptivity requires mapping service interfaces onto multiple implementations, truly alternative interpretations of the same functionality. We then analyse two design solutions in which the alternative implementations are, respectively, full-fledged services and local components of a single service. We associate the latter with lower development costs and increased binding flexibility, and outline a strategy to deploy them dynamically as the payload of service plugins. The result is an infrastructure in which services exhibit multiple behaviours, know how to select the most appropriate behaviour, and can seamlessly learn new behaviours