Metrics and models to support the development of hybrid information systems

The research described here concerns the development of metrics and models to support the development of hybrid (conventional/knowledge based) integrated systems. The thesis argues from the point that, although it is well known that estimating the cost, duration and quality of information systems is a difficult task, it is far from clear what sorts of tools and techniques would adequately support a project manager in the estimation of these properties. A literature review shows that metrics (measurements) and estimating tools have been developed for conventional systems since the 1960s while there has been very little research on metrics for knowledge based systems (KBSs). Furthermore, although there are a number of theoretical problems with many of the `classic' metrics developed for conventional systems, it also appears that the tools which such metrics can be used to develop are not widely used by project managers. A survey was carried out of large UK companies which confirmed this continuing state of affairs. Before any useful tools could be developed, therefore, it was important to find out why project managers were not using these tools already. By characterising those companies that use software cost estimating (SCE) tools against those which could but do not, it was possible to recognise the involvement of the client/customer in the process of estimation. Pursuing this point, a model of the early estimating and planning stages (the EEPS model) was developed to test exactly where estimating takes place. The EEPS model suggests that estimating could take place either before a fully-developed plan has been produced, or while this plan is being produced. If it were the former, then SCE tools would be particularly useful since there is very little other data available from which to produce an estimate. A second survey, however, indicated that project managers see estimating as being essentially the latter at which point project management tools are available to support the process. It would seem, therefore, that SCE tools are not being used because project management tools are being used instead. The issue here is not with the method of developing an estimating model or tool, but; in the way in which "an estimate" is intimately tied to an understanding of what tasks are being planned. Current SCE tools are perceived by project managers as targetting the wrong point of estimation, A model (called TABATHA) is then presented which describes how an estimating tool based on an analysis of tasks would thus fit into the planning stage. The issue of whether metrics can be usefully developed for hybrid systems (which also contain KBS components) is tested by extending a number of "classic" program size and structure metrics to a KBS language, Prolog. Measurements of lines of code, Halstead's operators/operands, McCabe's cyclomatic complexity, Henry & Kafura's data flow fan-in/out and post-release reported errors were taken for a set of 80 commercially-developed LPA Prolog programs: By re~defining the metric counts for Prolog it was found that estimates of program size and error-proneness comparable to the best conventional studies are possible. This suggests that metrics can be usefully applied to KBS languages, such as Prolog and thus, the development of metncs and models to support the development of hybrid information systems is both feasible and useful.

An approach to the development of expert systems within production planning and control

The thesis presents an account of an attempt to utilize expert systems within the domain of production planning and control. The use of expert systems was proposed due to the problematical nature of a particular function within British Steel Strip Products' Operations Department: the function of Order Allocation, allocating customer orders to a production week and site. Approaches to tackling problems within production planning and control are reviewed, as are the general capabilities of expert systems. The conclusions drawn are that the domain of production planning and control contains both `soft' and `hard' problems, and that while expert systems appear to be a useful technology for this domain, this usefulness has by no means yet been demonstrated. Also, it is argued that the main stream methodology for developing expert systems is unsuited for the domain. A problem-driven approach is developed and used to tackle the Order Allocation function. The resulting system, UAAMS, contained two expert components. One of these, the scheduling procedure was not fully implemented due to inadequate software. The second expert component, the product routing procedure, was untroubled by such difficulties, though it was unusable on its own; thus a second system was developed. This system, MICRO-X10, duplicated the function of X10, a complex database query routine used daily by Order Allocation. A prototype version of MICRO-X10 proved too slow to be useful but allowed implementation and maintenance issues to be analysed. In conclusion, the usefulness of the problem-driven approach to expert systems development within production planning and control is demonstrated but restrictions imposed by current expert system software are highlighted in that the abilities of such software to cope with `hard' scheduling constructs and also the slow processing speeds of such software can restrict the current usefulness of expert systems within production planning and control.

Business information systems:technology, development and management in the E-business

Information technology is at the centre of today’s business environment. The increasing importance of e-commerce and the integration of information systems in all areas of a business means it is crucial for managers to understand and implement IS (information systems). This major text, now in its second edition, provides the skills and knowledge necessary to choose the right systems, and to develop and manage them effectively. Business Information Systems: Technology, Development and Management assumes no prior knowledge of IS or IT, and emphasises the importance of IS to management decision making. It takes a 3 part structure: Part One covers hardware and software technologies; Part Two looks at information systems analysis and design; and Part Three describes the strategic management of IS. This successful format allows each section to be studied alongside individual modules, and enables students to focus clearly on specific areas and use the book for more than one course. This book is suitable for college students, undergraduate degree and postgraduate students taking courses with modules in the practical IT skills of selection, implementation, management and use of BIS. The practical sections are also of use to managers in industry involved in the development and use of IS.

Minimizing nasty surprises with better informed decision-making in self-adaptive systems

Designers of self-adaptive systems often formulate adaptive design decisions, making unrealistic or myopic assumptions about the system's requirements and environment. The decisions taken during this formulation are crucial for satisfying requirements. In environments which are characterized by uncertainty and dynamism, deviation from these assumptions is the norm and may trigger 'surprises'. Our method allows designers to make explicit links between the possible emergence of surprises, risks and design trade-offs. The method can be used to explore the design decisions for self-adaptive systems and choose among decisions that better fulfil (or rather partially fulfil) non-functional requirements and address their trade-offs. The analysis can also provide designers with valuable input for refining the adaptation decisions to balance, for example, resilience (i.e. Satisfiability of non-functional requirements and their trade-offs) and stability (i.e. Minimizing the frequency of adaptation). The objective is to provide designers of self adaptive systems with a basis for multi-dimensional what-if analysis to revise and improve the understanding of the environment and its effect on non-functional requirements and thereafter decision-making. We have applied the method to a wireless sensor network for flood prediction. The application shows that the method gives rise to questions that were not explicitly asked before at design-time and assists designers in the process of risk-aware, what-if and trade-off analysis.

The emergence of knowledge exchange:an agent-based model of a software market

We investigate knowledge exchange among commercial organizations, the rationale behind it, and its effects on the market. Knowledge exchange is known to be beneficial for industry, but in order to explain it, authors have used high-level concepts like network effects, reputation, and trust. We attempt to formalize a plausible and elegant explanation of how and why companies adopt information exchange and why it benefits the market as a whole when this happens. This explanation is based on a multiagent model that simulates a market of software providers. Even though the model does not include any high-level concepts, information exchange naturally emerges during simulations as a successful profitable behavior. The conclusions reached by this agent-based analysis are twofold: 1) a straightforward set of assumptions is enough to give rise to exchange in a software market, and 2) knowledge exchange is shown to increase the efficiency of the market.

Requirements-aware systems:a research agenda for RE for self-adaptive systems

Requirements are sensitive to the context in which the system-to-be must operate. Where such context is well-understood and is static or evolves slowly, existing RE techniques can be made to work well. Increasingly, however, development projects are being challenged to build systems to operate in contexts that are volatile over short periods in ways that are imperfectly understood. Such systems need to be able to adapt to new environmental contexts dynamically, but the contextual uncertainty that demands this self-adaptive ability makes it hard to formulate, validate and manage their requirements. Different contexts may demand different requirements trade-offs. Unanticipated contexts may even lead to entirely new requirements. To help counter this uncertainty, we argue that requirements for self-adaptive systems should be run-time entities that can be reasoned over in order to understand the extent to which they are being satisfied and to support adaptation decisions that can take advantage of the systems' self-adaptive machinery. We take our inspiration from the fact that explicit, abstract representations of software architectures used to be considered design-time-only entities but computational reflection showed that architectural concerns could be represented at run-time too, helping systems to dynamically reconfigure themselves according to changing context. We propose to use analogous mechanisms to achieve requirements reflection. In this paper we discuss the ideas that support requirements reflection as a means to articulate some of the outstanding research challenges.

Towards requirements aware systems:run-time resolution of design-time assumptions

In earlier work we proposed the idea of requirements-aware systems that could introspect about the extent to which their goals were being satisfied at runtime. When combined with requirements monitoring and self adaptive capabilities, requirements awareness should help optimize goal satisfaction even in the presence of changing run-time context. In this paper we describe initial progress towards the realization of requirements-aware systems with REAssuRE. REAssuRE focuses on explicit representation of assumptions made at design time. When such assumptions are shown not to hold, REAssuRE can trigger system adaptations to alternative goal realization strategies.

Model-driven software adaptation:report on the workshop M-ADAPT at ECOOP 2007

This first edition of the workshop Model-driven Software Adaptation (M-ADAPT'07) took place in the Technische Universität Berlin with the International Conference ECOOP'07 in the beautiful and buzzing city of Berlin, on the 30th of July, 2007. The workshop was organized by Gordon Blair, Nelly Bencomo, and Robert France. Participants explored how to develop appropriate model-driven approaches to model, analyze, and validate the volatile properties of the behaviour of adaptive systems and its environments. This report gives an overview of the presentations as well as an account of the fruitful discussions that took place at M-ADAPT'07. © 2008 Springer-Verlag Berlin Heidelberg.

Using architecture models to support the generation and operation of component-based adaptive systems

Modelling architectural information is particularly important because of the acknowledged crucial role of software architecture in raising the level of abstraction during development. In the MDE area, the level of abstraction of models has frequently been related to low-level design concepts. However, model-driven techniques can be further exploited to model software artefacts that take into account the architecture of the system and its changes according to variations of the environment. In this paper, we propose model-driven techniques and dynamic variability as concepts useful for modelling the dynamic fluctuation of the environment and its impact on the architecture. Using the mappings from the models to implementation, generative techniques allow the (semi) automatic generation of artefacts making the process more efficient and promoting software reuse. The automatic generation of configurations and reconfigurations from models provides the basis for safer execution. The architectural perspective offered by the models shift focus away from implementation details to the whole view of the system and its runtime change promoting high-level analysis. © 2009 Springer Berlin Heidelberg.

Market-awareness in service-based systems

Service-based systems are applications built by composing pre-existing services. During design time and according to the specifications, a set of services is selected. Both, service providers and consumers exist in a service market that is constantly changing. Service providers continuously change their quality of services (QoS), and service consumers can update their specifications according to what the market is offering. Therefore, during runtime, the services are periodically and manually checked to verify if they still satisfy the specifications. Unfortunately, humans are overwhelmed with the degree of changes exhibited by the service market. Consequently, verification of the compliance specification and execution of the corresponding adaptations when deviations are detected cannot be carried out in a manual fashion. In this work, we propose a framework to enable online awareness of changes in the service market in both consumers and providers by representing them as active software agents. At runtime, consumer agents concretize QoS specifications according to the available market knowledge. Services agents are collectively aware of themselves and of the consumers' requests. Moreover, they can create and maintain virtual organizations to react actively to demands that come from the market. In this paper we show preliminary results that allow us to conclude that the creation and adaptation of service-based systems can be carried out by a self-organized service market system. © 2012 IEEE.

Tracing requirements for adaptive systems using claims

The complexity of environments faced by dynamically adaptive systems (DAS) means that the RE process will often be iterative with analysts revisiting the system specifications based on new environmental understanding product of experiences with experimental deployments, or even after final deployments. An ability to trace backwards to an identified environmental assumption, and to trace forwards to find the areas of a DAS's specification that are affected by changes in environmental understanding aids in supporting this necessarily iterative RE process. This paper demonstrates how claims can be used as markers for areas of uncertainty in a DAS specification. The paper demonstrates backward tracing using claims to identify faulty environmental understanding, and forward tracing to allow generation of new behaviour in the form of policy adaptations and models for transitioning the running system. © 2011 ACM.

Genie:supporting the model driven development of reflective, component-based adaptive systems

Engineering adaptive software is an increasingly complex task. Here, we demonstrate Genie, a tool that supports the modelling, generation, and operation of highly reconfigurable, component-based systems. We showcase how Genie is used in two case-studies: i) the development and operation of an adaptive flood warning system, and ii) a service discovery application. In this context, adaptation is enabled by the Gridkit reflective middleware platform.

Dynamic decision networks for decision-making in self-adaptive systems:a case study

Bayesian decision theory is increasingly applied to support decision-making processes under environmental variability and uncertainty. Researchers from application areas like psychology and biomedicine have applied these techniques successfully. However, in the area of software engineering and speci?cally in the area of self-adaptive systems (SASs), little progress has been made in the application of Bayesian decision theory. We believe that techniques based on Bayesian Networks (BNs) are useful for systems that dynamically adapt themselves at runtime to a changing environment, which is usually uncertain. In this paper, we discuss the case for the use of BNs, speci?cally Dynamic Decision Networks (DDNs), to support the decision-making of self-adaptive systems. We present how such a probabilistic model can be used to support the decision making in SASs and justify its applicability. We have applied our DDN-based approach to the case of an adaptive remote data mirroring system. We discuss results, implications and potential bene?ts of the DDN to enhance the development and operation of self-adaptive systems, by providing mechanisms to cope with uncertainty and automatically make the best decision.

Proactive environmental systems:the next generation of environmental monitoring

In this article we envision factors and trends that shape the next generation of environmental monitoring systems. One key factor in this respect is the combined effect of end-user needs and the general development of IT services and their availability. Currently, an environmental (monitoring) system is assumed to be reactive. It delivers measurement data and computational results only if the user explicitly asks for it either by query or subscription. There is a temptation to automate this by simply pushing data to end-users. This, however, leads easily to an "advertisement strategy", where data is pushed to end-users regardless of users' needs. Under this strategy, the mere amount of received data obfuscates the individual messages; any "automatic" service, regardless of its fitness, overruns a system that requires the user's initiative. The foreseeable problem is that, unless there is no overall management, each new environmental service is going to compete for end-users' attention and, thus, inadvertently hinder the use of existing services. As the main contribution we investigate the nature of proactive environmental systems, and how they should be designed to avoid the aforementioned problem. We also discuss how semantics, participatory sensing, uncertainty management, and situational awareness link to proactive environmental systems. We illustrate our proposals with some real-life examples.

EPiCS:engineering proprioception in computing systems

Modern compute systems continue to evolve towards increasingly complex, heterogeneous and distributed architectures. At the same time, functionality and performance are no longer the only aspects when developing applications for such systems, and additional concerns such as flexibility, power efficiency, resource usage, reliability and cost are becoming increasingly important. This does not only raise the question of how to efficiently develop applications for such systems, but also how to cope with dynamic changes in the application behaviour or the system environment. The EPiCS Project aims to address these aspects through exploring self-awareness and self-expression. Self-awareness allows systems and applications to gather and maintain information about their current state and environment, and reason about their behaviour. Self-expression enables systems to adapt their behaviour autonomously to changing conditions. Innovations in EPiCS are based on systematic integration of research in concepts and foundations, customisable hardware/software platforms and operating systems, and self-aware networking and middleware infrastructure. The developed technologies are validated in three application domains: computational finance, distributed smart cameras and interactive mobile media systems. © 2012 IEEE.