to investigate the role of values in technology acceptance in general and in the context of the UK Covid Track and Trace App. A survey and interview study was conducted to elicit users’ perceptions of values in general, values in relation to choice of IT products and values which were influenced the decision to download (or not) the NHS Covid-19 Track and Trace App. Other non-value issues such as utility, price and recommendations were considered. Users’ value in life differ slightly from those considered important for selecting IT products. For general IT product decisions, functionality, trust and price with values equality, security and sustainability were important. For the Covid-19 App decision two values, helpfulness and equality, with recommendations/trust and operating system compatibility, were the main influences. Interview data indicated that downloader users were motivated by social responsibility and utility – being able to access workplaces and leisure venues – while non-downloaders had little perceived need for the App, combined with mistrust of the App's provenance (NHS and the Government) linked to security and privacy concerns. The implications for values in technology acceptance decisions are discussed.

A new focus for RE is investigated as ‘soft’ requirements which extends non-functional requirements/soft goals with a collection of people-oriented phenomena: values, motivations, emotions, and other socio-political issues that may influence the requirements specification. The convergence of RE with user experience (HCI) and technology acceptance from the information systems literature is reviewed from a temporal perspective: pre-use, through initial to longer-term use. A taxonomy of soft requirements is proposed that extends non-functional requirements and soft-goal concepts to direct attention towards user characteristics and beliefs that may have implications for functional as well as system support requirements, such as training, help, explanation and trust in software. A timeline model of soft and hard (functional) requirements is presented with a focus on customization, adaptation and other soft requirements to, improve product acceptance and persuade users to take appropriate action. The paper concludes with a research agenda for soft requirements to improve the probability of system acceptance and the effectiveness of applications that aim to influence people’s decisions and behaviour in internet apps and other discretionary-use applications.

Abstract Self-adaptive systems (SASs) are increasingly leveraging autonomy in their decision-making to manage uncertainty in their operating environments. A key problem with SASs is ensuring their requirements remain satisfied as they adapt. The trade-off analysis of the non-functional requirements (NFRs) is key to establish balance among them. Further, when performing the trade-offs it is necessary to know the importance of each NFR to be able to resolve conflicts among them. Such trade-off analyses are often built upon optimisation methods, including decision analysis and utility theory. A problem with these techniques is that they use a single-scalar utility value to represent the overall combined priority for all the NFRs. However, this combined scalar priority value may hide information about the impacts of the environmental contexts on the individual NFRs’ priorities, which may change over time. Hence, there is a need for support for runtime, autonomous reasoning about the separate priority values for each NFR, while using the knowledge acquired based on evidence collected. In this paper, we propose Pri-AwaRE, a self-adaptive architecture that makes use of Multi-Reward Partially Observable Markov Decision Process (MR-POMDP) to perform decision-making for SASs while offering awareness of NFRs’ priorities. MR-POMDP is used as a priority-aware runtime specification model to support runtime reasoning and autonomous tuning of the distinct priority values of NFRs using a vector-valued reward function. We also evaluate the usefulness of our Pri-AwaRE approach by applying it to two substantial example applications from the networking and IoT domains.

The main objective of decision-making in a self-adaptive system (SAS) is to continuously satisfy its requirements under environmental uncertainty. As the run-time context changes, the system may need to re-configure itself by making trade-offs between the non-functional requirements (NFRs) based on their individual priorities for satisfaction. We demonstrate Pri-AwaRE as an approach to support priority-aware decision-making in SASs by providing explicit runtime modelling and reasoning of individual priorities of NFRs. The approach also supports autonomous tuning of the priorities under dynamic situations to maintain the required satisfaction levels of NFRs. In this paper, we showcase how Pri-AwaRE is used in a substantial industrial case of Remote Mirroring using a simulation tool called RDMSim. Our results show that Pri-AwaRE offers the required satisfaction levels of NFRs by autonomously tuning of NFRs’ priorities according to new runtime environmental contexts.

We report experience in requirements elicitation of domain knowledge from experts in clinical and cognitive neurosciences. The elicitation target was a causal model for early signs of dementia indicated by changes in user behaviour and errors apparent in logs of computer activity. A Delphi-style process consisting of workshops with experts followed by a questionnaire was adopted. The paper describes how the elicitation process had to be adapted to deal with problems encountered in terminology and limited consensus among the experts. In spite of the difficulties encountered, a partial causal model of user behavioural pathologies and errors was elicited. This informed requirements for configuring data- and text-mining tools to search for the specific data patterns. Lessons learned for elicitation from experts are presented, and the implications for requirements are discussed as “unknown unknowns”, as well as configuration requirements for directing data-/text-mining tools towards refining awareness requirements in healthcare applications.

Various types of saccadic paradigms, in particular, Prosaccade and Antisaccade tests are widely used in Pathophysiology and Psychology. Despite been widely used, there has not been a standard tool for processing and analyzing the eye tracking data obtained from saccade tests. We describe an open-source software for extracting and analyzing the eye movement data of different types of saccade tests that can be used to extract and compare participants' performance and various task-related measures across participants. We further demonstrate the utility of the software by using it to analyze the data from an antisaccade, and a recent distractor experiment.

Many innovative software products are conceived, developed and deployed without any conventional attempt to elicit stakeholder requirements. Rather, they are the result of the vision and intuition of a small number of creative individuals, facilitated by the emergence of a new technology. In this paper we consider how the conditions that enable new products' emergence might be better anticipated, making innovations a little less reliant on individual vision and a little more informed by stakeholder need. This is particularly important where a new technology would have the potential for social impact, good or bad. Speculative design seeks to explore this landscape. We describe a case study using a variant called design fiction to explore how plausible new technologies might impact on dementia care.

Online discussions about software applications generate a large amount of requirements-related information. This information can potentially be usefully applied in requirements engineering; however currently, there are few systematic approaches for extracting such information. To address this gap, we propose Canary, an approach for extracting and querying requirements-related information in online discussions. The highlight of our approach is a high-level query language that combines aspects of both requirements and discussion in online forums. We give the semantics of the query language in terms of relational databases and SQL. We demonstrate the usefulness of the language using examples on real data extracted from online discussions. Our approach relies on human annotations of online discussions. We highlight the subtleties involved in interpreting the content in online discussions and the assumptions and choices we made to effectively address them. We demonstrate the feasibility of generating high-quality annotations by obtaining them from lay Amazon Mechanical Turk users.

Interactions among stakeholders and engineers is key to Requirements engineering (RE). Increasingly, such interactions take place online, producing large quantities of qualitative (natural language) and quantitative (e.g., votes) data. Although a rich source of requirements-related information, extracting such information from online forums can be nontrivial.We propose Canary, a tool-assisted approach, to facilitate systematic extraction of requirements-related information from online forums via high-level queries. Canary (1) adds structure to natural language content on online forums using an annotation schema combining requirements and argumentation ontologies, (2) stores the structured data in a relational database, and (3) compiles high-level queries in Canary syntax to SQL queries that can be run on the relational database.We demonstrate key steps in Canary workflow, including (1) extracting raw data from online forums, (2) applying annotations to the raw data, and (3) compiling and running interesting Canary queries that leverage the social aspect of the data.

We report the strategies and outcomes of requirements analysis in the SAMS project, which aims to detect early signs of dementia from records of user behaviour derived from monitoring home computer activity. Initial requirements elicitation specified a complex monitoring system in the genre of awareness requirements. As the complexity of the requirements for interpreting user activity became apparent, we revised our strategy towards an iterative refinement driven by analysis of recorded data. We propose that analysis of complex awareness requirements may necessitate a tool-driven approach where data mining software is configured to discover new requirements. Requirements for data mining and data analysis in SAMS are described. Application of the conceptual architecture for directing requirements analysis strategy in complex system with human in the loop for data analysis and adaptation is investigated. The implications for the extended view for RE are discussed with reference to systems with potentially unknown requirements. A research road map is outlined for the convergence of data mining and RE.

Dementia is a serious threat to social sustainability. As life expectancy increases, more people are developing dementia. At the same time, demographic change is reducing the economically active part of the population. Care of people with dementia imposes great emotional and financial strain on sufferers, their families and society at large. In response, significant research resources are being focused on dementia. One research thread is focused on using computer technology to monitor people in at-risk groups to improve rates of early diagnosis. In this paper we provide an overview of dementia monitoring research and identify a set of scientific challenges for the engineering of dementia-monitoring software, with implications for other mental health self-management systems.

Novel envisioned systems face the risk of rejection by their target user community and the requirements engineer must be sensitive to the factors that will determine acceptance or rejection. Conventionally, technology acceptance is determined by perceived usefulness and ease-of-use, but in some domains other factors play an important role. In healthcare systems, particularly, ethical and emotional factors can be crucial. In this paper we describe an approach to requirements discovery that we developed for such systems. We describe how we have applied our approach to a novel system to passively monitor users for signs of cognitive decline consistent with the onset of dementia. A key challenge was eliciting users' reactions to emotionally charged events never before experienced by them at first hand. Our goal was to understand the range of users' emotional responses and their values and motivations, and from these formulate requirements that would maximise the likelihood of acceptance of the system. The problem was heightened by the fact that the key stakeholders were elderly people who represent a poorly studied user constituency. We discuss the elicitation and analysis methodologies used, and our experience with tool support. We conclude by reflecting on the affect issues for RE and for technology acceptance.

Requirements elicitation research is reviewed using a framework categorising the relative `knowness' of requirements specification and Common Ground discourse theory. The main contribution of this survey is to review requirements elicitation from the perspective of this framework and propose a road map of research to tackle outstanding elicitation problems involving tacit knowledge. Elicitation techniques (interviews, scenarios, prototypes, etc.) are investigated, followed by representations, models and support tools. The survey results suggest that elicitation techniques appear to be relatively mature, although new areas of creative requirements are emerging. Representations and models are also well established although there is potential for more sophisticated modelling of domain knowledge. While model-checking tools continue to become more elaborate, more growth is apparent in NL tools such as text mining and IR which help to categorize and disambiguate requirements. Social collaboration support is a relatively new area that facilitates categorisation, prioritisation and matching collections of requirements for product line versions. A road map for future requirements elicitation research is proposed investigating the prospects for techniques, models and tools in green-field domains where few solutions exist, contrasted with brown-field domains where collections of requirements and products already exist. The paper concludes with remarks on the possibility of elicitation tackling the most difficult question of `unknown unknown' requirements.

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.

Summary form only given. Due to increasing complexity of software in embedded systems, the software development requires approaches that can manage that complexity in a similar way as this is done in general-purpose software, but at the same time provide support for embedded systems specifics. In this paper we give a short overview of a component-based approach that meets these requirements.

Requirements awareness should help optimize requirements satisfaction when factors that were uncertain at design time are resolved at runtime. We use the notion of claims to model assumptions that cannot be verified with confidence at design time. By monitoring claims at runtime, their veracity can be tested. If falsified, the effect of claim negation can be propagated to the system's goal model and an alternative means of goal realization selected automatically, allowing the dynamic adaptation of the system to the prevailing environmental context.

Computational reflection is a well-established technique that gives a program the ability to dynamically observe and possibly modify its behaviour. To date, however, reflection is mainly applied either to the software architecture or its implementation. We know of no approach that fully supports requirements reflection- that is, making requirements available as runtime objects. Although there is a body of literature on requirements monitoring, such work typically generates runtime artefacts from requirements and so the requirements themselves are not directly accessible at runtime. In this paper, we define requirements reflection and a set of research challenges. Requirements reflection is important because software systems of the future will be self-managing and will need to adapt continuously to changing environmental conditions. We argue requirements reflection can support such self-adaptive systems by making requirements first-class runtime entities, thus endowing software systems with the ability to reason about, understand, explain and modify requirements at runtime.

The identification of abstractions, i.e. terms that have a particular significance in a given domain, and such that they can indirectly characterize the most salient features of the document in which they appear, has often been recognized as a useful tool in the analysis of domain descriptions and requirements documents in software development. In this paper we propose a new technique for the identification of single- and multi-word abstractions named Relevance driven abstraction identification (RAI) and a corresponding tool implementation, present an experiment comparing the effectiveness of our technique with human judgement and with a different technique proposed in the literature, and discuss a number of ways in which the abstractions so identified can be used to good profit in requirements engineering.

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.

Much medical knowledge is contained within available literature, such as clinical guidelines and protocols. Recently, an interest has been developed in automatic content extraction to construct ontologies of this knowledge to make it more widely available. With groups of domain experts distributed geographically, and the growing amount of medical literature, an important challenge is to develop collaborative workflows to support ways for domain experts to contribute in the ontology learning process. This paper presents a collaborative workflow for ontology learning based on coupling an Ontology Learning Tool (OntoLancs) with and Ontology engineer (Protégé) to provide semi-automatic support for text mining and a collaborative tool to model formal ontologies. The work presented in this paper was evaluated with a case study on a Clinical Practice Guideline of Diabetic Retinopathy. The major benefits of coupling OntoLancs with Protégé are: a) a higher level of automation in the creation of domain ontologies and models, and b) strengthened communication and information exchange among domain experts that are physically distributed. Validations of user experiences indicate the applicability of our approach.

Self-adaptive systems have the capability to autonomously modify their behaviour at run-time in response to changes in their environment. Self-adaptation is particularly necessary for applications that must run continuously, even under adverse conditions and changing requirements; sample domains include automotive systems, telecommunications, and environmental monitoring systems. While a few techniques have been developed to support the monitoring and analysis of requirements for adaptive systems, limited attention has been paid to the actual creation and specification of requirements of self-adaptive systems. As a result, self-adaptivity is often constructed in an ad-hoc manner. In this paper, we argue that a more rigorous treatment of requirements explicitly relating to self-adaptivity is needed and that, in particular, requirements languages for self-adaptive systems should include explicit constructs for specifying and dealing with the uncertainty inherent in self-adaptive systems. We present RELAX, a new requirements language for self-adaptive systems and illustrate it using examples from the smart home domain.

This mini-tutorial introduces Web services and service-centric systems, identifies their impact on requirements engineering, and introduces new tools and techniques for engineer requirements for service-centric systems.

Domain analysis involves not only looking at standard requirements documents (e.g., use case specifications) but also at customer information packs, market analyses, etc. Looking across all these documents and deriving, in a practical and scalable way, a feature model that is comprised of coherent abstractions is a fundamental and non-trivial challenge. We conduct an exploratory study to investigate the suitability of Information Retrieval (IR) techniques for scalable identification of commonalities and variabilities in requirement specifications for software product lines. Accordingly, based on observations derived from industrial experience and on state-of-the-art research and practice, we also propose an initial framework, leveraging IR to systematically abstract requirements from existing specifications of a given domain into a feature model. We evaluate this framework, present a roadmap for its further extension, and formulate hypotheses to guide future work in exploring IR techniques for domain analysis.

Service-centric computing is developing and maturing rapidly as a paradigm for developing distributed systems. In recent years there has been a rapid growth in the number and types of processes being proposed to support aspects of SOC. Many of these processes require that services be modelled in a particular way and this puts great pressure on traditional notions of service specification, questioning the very nature of how services should be described for potential consumers. We present a technique for addressing this theoretical and practical bottleneck: faceted service specification. This allows different specifications to exist side-by-side if they are needed, yet places little obligation on the service provider to support specifications that are judged to be of little or no value. We show how faceted service specification is being used in the SeCSE project to support advanced service-centric system development activities.

The advent of and growing interest in service- oriented architectures (SOA) present business leaders with a number of problems. They promise to deliver hitherto unseen business process agility, but at the risk of making investment in existing systems obsolete. The established orthodoxy is that the maintenance problem presented by installed systems is about finding an acceptable balance between risk involved in evolving the system and benefits offered by the update. SOAs represent a "paradigm-shift" and, as such, present a more complicated problem: how to minimise the risk to their investment (existing software systems) and exploit the benefits of migrating to SOA. We provide a review of a number of approaches that may contribute to a pragmatic strategy for addressing the problem and outline the significant challenges that remain.

Pre-requirements specification tracing concerns the identification and maintenance of relationships between requirements and the knowledge and information used by analysts to inform the requirements' formulation. Some of the knowledge used is tacit and therefore hard to identify and associate with requirements. This paper presents a tool for retrospectively identifying pre-requirements traces from requirements to their respective source material. We posit that poorly sourced requirements may indicate a requirement based on tacit knowledge. We present a preliminary evaluation of our tools performance using a case study

As a branch of engineering cybernetics, automatic control theory has been extensively applied to improve product, increase productivity and rationalize management. As a first try, this paper intends to adapt the principles of conventional control theory to the field of software process, and use them to define a requirement process control system, its dynamic and steady-state performance, and steps in designing, analyzing and improving such a system. Preliminary studies show that more requirements engineering (RE) process activities relating to measuring elements, including those in feedback compensation and organization support, need to be introduced, recommended and selected. The results of this research can be used to guide the establishment and improvement of RE processes, compare different requirement process solutions quantitatively, develop methods for evaluating benefits from process improvements, and structure the application of knowledge about RE.

Like any other database application, object database applications are subject to evolution. Evolution, however, is a critical requirement in object-oriented databases as it is a fundamental characteristic of complex applications such as computer-aided design and manufacturing (CAD/CAM) and office information systems. Object-oriented databases are inherently suited to supporting such applications. In this paper we present a database evolution taxonomy for object-oriented databases. We describe a conceptual database model and use it to define the taxonomy. We also present the various invariants and rules governing the various evolution operations. The execution sequence of rules is described. An implementation of the database model and the evolution taxonomy in the Semi-Autonomous Database Evolution System (SADES), is discussed. The implementation employs aspect-oriented programming techniques to provide a flexible means of transforming objects upon evolution, and implementing some application-specific evolution primitives. A case study compares the evolution taxonomy with existing evolution approaches. The comparison demonstrates that the taxonomy and its corresponding implementation in SADES provide improved coverage of the fundamental evolution operations to which an object database might be subjected. At the same time, erosion of the database structure is avoided by maintaining a coherent and comprehensible view of historical changes. Copyright © 2005 John Wiley & Sons, Ltd.

Requirements engineering's continuing dependence on natural language description has made it the focus of several efforts to apply language engineering techniques. The raw textual material that forms an input to early phase requirements engineering and which informs the subsequent formulation of the requirements is inevitably uncontrolled and this makes its processing very hard. Nevertheless, sufficiently robust techniques do exist that can be used to aid the requirements engineer provided that the scope of what can be achieved is understood. In this paper, we show how combinations of lexical and shallow semantic analysis techniques developed from corpus linguistics can help human analysts acquire the deep understanding needed as the first step towards the synthesis of requirements.

Effective RE must reconcile the need to achieve separation of concerns with the need to satisfy broadly scoped requirements and constraints. Techniques such as use cases and viewpoints help achieve separation of stakeholders' concerns but ensuring their consistency with global requirements and constraints is largely unsupported. We build on recent work that has emerged from the aspect-oriented programming (AOP) community to propose a general model for aspect oriented requirements engineering (AORE). The model supports separation of crosscutting functional and non-functional properties at the requirements level. We argue that early separation of such crosscutting properties supports effective determination of their mapping and influence on artefacts at later development stages. A realisation of the model based on a case study of a toll collection system is presented.

Discusses the notion of software process inconsistency and suggests that inconsistencies in software processes are inevitable and sometimes desirable. We present an approach to process analysis that helps discover different perceptions of a software process and that supports the discovery of process inconsistencies and process improvements stimulated by these inconsistencies. By analogy with viewpoints for requirements engineering that allow multiple perspectives on a software system specification to be managed, we have developed the notion of process viewpoints that provide multi-perspective descriptions of software processes. A process viewpoint includes a statement of focus or "world view", a set of sources of process information, a process description and a set of organizational concerns that represent goals or constraints on the process analysis. We present a description and rationale of process viewpoints, discuss the process of applying process viewpoints for process understanding, and illustrate the overall approach using part of a case study drawn from industrial processes that are part of a safety-critical system development.

Databases and their applications form one of the most important classes of computer systems yet they have received relatively little attention from the HCI community. They have nevertheless spawned some notably innovative user interfaces and it is interesting to examine these in the light of contemporary HCI issues. The paper addresses the relationship between HCI and database systems, reviews some of the major themes running through existing database user interfaces and postulates some issues which are likely to be important to database usability in the future. The underlying argument is that databases are sufficiently different from other classes of application to necessitate a raft of user interface techniques specifically for the needs of database users which would reward increased attention by the HCI community.

This paper discusses an innovative experiment where sociologists were actively involved in the requirements analysis for an interactive software system to support the work of air traffic controllers. Air traffic control is intrinsically cooperative and our work involved an analysis of that process from a social perspective and the development of a prototype user interface for air traffic controllers’ interaction with a flight information system. As part of the analysis process, sociologists were involved in ethnographic studies of work and discovered subtle and complex patterns of cooperation which, we suspect, would not have been discovered using structured methods for requirements analysis. From a software development perspective, we describe how the input from the sociologists was essential for understanding the real automation requirements, discuss the difficulties of inter-disciplinary cooperative working and suggest how social analysis can be integrated in the interactive systems design process.

Experiences from an interdisciplinary project involving software engineers and sociologists are reported. The project is concerned with discovering the requirements of a user interface to a flight database which is used to provide real-time information to air-traffic controllers. The sociologists are conducting an ethnographic analysis of the activity of air-traffic control, and this is being used for the development of a prototype system. An overview of the project is given, the contribution of sociologists to requirements engineering is discussed, and tool support which will allow ethnographic observations to be integrated into the requirements engineering process is suggested.>

Tools which provide graphical editing techniques for the design of user interface presentations are increasingly commonplace. Such tools vary widely in the mechanisms used to define user interfaces and while some are general purpose, others are targeted at particular application domains. Designers faced with varying requirements must choose one tool and live with its shortcomings, purchase a number of different tools, or implement their own. The paper describes an approach to facilitating the latter by providing a library of augmented user interface components called MOG objects which embody both end-user and editing semantics. User interface design tools based on this approach need only provide mechanisms for composing MOG objects into user interfaces and the addition of any other, higher-level functionality. MOG-based user interfaces retain an in-built editing capability and are inherently tailorable.

This paper relates experiences of a project where an ethnographic study of air traffic controllers is being used to inform the design of the controllers' interface to the flight data base. We outline the current UK air traffic control system, discuss the ethnographic work we have undertaken studying air traffic control as a cooperative activity, describe some of the difficulties in collaboration between software developers and sociologists and show how the ethnographic studies have influenced the systems design process. Our conclusions are that ethnographic studies are helpful in informing the systems design process and may produce insights which contradict conventional thinking in systems design. KEYWORDS Air Traffic Control, Systems Design, Ethnography INTRODUCTION One of the most significant influences of CSCW has been to lend a respectability amongst software developers to sociological methods of empirical research. The contribution of sociology, and anthropology, is through the de...

A range of architectures have emerged which support realtime cooperative user interfaces. These architectures have tended to centralise the management of the interface and thus provide only limited support for user-centred development and interface tailoring. This paper considers the problems associated with the development of tailorable cooperative interfaces and proposes an architecture which allows such interfaces to be developed using an incremental, user-centred approach. The architecture presented in this paper has emerged within the context of a project investigating cooperative interface development for UK air traffic control. We conclude that the architecture is equally applicable to other Command and Control domains, where a shared information space forms the focus for the work taking place. KEYWORDS Multi-user interfaces, CSCW architectures, Command and Control systems, Database visualisation. INTRODUCTION The merging of computer and communications technology and the develop...