A situational approach for the definition and tailoring of a data-driven software evolution method

Successful software evolution heavily depends on the selection of the right features to be included in the next release. Such selection is difficult, and companies often report bad experiences about user acceptance. To overcome this challenge, there is an increasing number of approaches that propose intensive use of data to drive evolution. This trend has motivated the SUPERSEDE method, which proposes the collection and analysis of user feedback and monitoring data as the baseline to elicit and prioritize requirements, which are then used to plan the next release. However, every company may be interested in tailoring this method depending on factors like project size, scope, etc. In order to provide a systematic approach, we propose the use of Situational Method Engineering to describe SUPERSEDE and guide its tailoring to a particular context.Peer ReviewedPostprint (author's final draft

Developing front-end Web 2.0 technologies to access services, content and things in the future Internet

The future Internet is expected to be composed of a mesh of interoperable web services accessible from all over the web. This approach has not yet caught on since global user?service interaction is still an open issue. This paper states one vision with regard to next-generation front-end Web 2.0 technology that will enable integrated access to services, contents and things in the future Internet. In this paper, we illustrate how front-ends that wrap traditional services and resources can be tailored to the needs of end users, converting end users into prosumers (creators and consumers of service-based applications). To do this, we propose an architecture that end users without programming skills can use to create front-ends, consult catalogues of resources tailored to their needs, easily integrate and coordinate front-ends and create composite applications to orchestrate services in their back-end. The paper includes a case study illustrating that current user-centred web development tools are at a very early stage of evolution. We provide statistical data on how the proposed architecture improves these tools. This paper is based on research conducted by the Service Front End (SFE) Open Alliance initiative

Alter ego, state of the art on user profiling: an overview of the most relevant organisational and behavioural aspects regarding User Profiling.

This report gives an overview of the most relevant organisational and\ud behavioural aspects regarding user profiling. It discusses not only the\ud most important aims of user profiling from both an organisation’s as\ud well as a user’s perspective, it will also discuss organisational motives\ud and barriers for user profiling and the most important conditions for\ud the success of user profiling. Finally recommendations are made and\ud suggestions for further research are given

Delphi Austria - An Example of Tailoring Foresight to the Needs of a Small Country

The world-wide diffusion and recognition of Technology Foresight suggests that it is of value for quite diverse types of economies and societies. Its merit as an important tool of strategic intelligence for policy-making also in small countries and transition economies depends on a careful tailoring to specific needs. Practice of Foresight is rather diverse also among small countries, but approaches tend to be more selective in scope, have more specific goals, and put greater emphasis on demand aspects than in bigger countries. Austria’s first systematic Foresight programme (completed in 1998) is an example of an innovative approach adapted to the needs of a small country. This contribution shows how Delphi Austria was tailored to a small economy which had undergone a successful catch-up process and how the Foresight process as well as its results have been utilised.Technology Foresight, Delphi method, small country, Austria, innovation, technology policy, implementation

Service Tailoring: Towards Personalized homecare Systems

Health monitoring and healthcare provisioning for the elderly at home have received increasingly attention. Since each elderly person is unique, with a unique lifestyle, living environment and health condition, personalization is an essential feature of homecare software services. Service tailoring, which is creating a new service to meet individual requirements may be achieved in a cost-effective and time-efficient manner if new services can be configured and composed from already existing services. In this paper, we propose an effective service tailoring process and architecture to personalize homecare services according to the individual care-receiver’s needs. In addition, we present a scenario to highlight the need for service tailoring and to demonstrate the feasibility of the proposed approach

Multilevel modelling of refusal and noncontact nonresponse in household surveys: evidence from six UK government surveys

This paper analyses household unit nonresponse and interviewer effects in six major UK government surveys using a multilevel multinomial modelling approach. The models are guided by current conceptual frameworks and theories of survey participation. One key feature of the analysis is the investigation of survey dependent and independent effects of household and interviewer characteristics, providing an empirical exploration of the leverage-salience theory. The analysis is based on the 2001 UK Census Link Study, a unique data source containing an unusually rich set of auxiliary variables, linking the response outcome of six surveys to census data, interviewer observation data and interviewer information, available for respondents and nonrespondents

A model and architecture for situation determination

Automatically determining the situation of an ad-hoc group of people and devices within a smart environment is a significant challenge in pervasive computing systems. Current approaches often rely on an environment expert to correlate the situations that occur with the available sensor data, while other machine learning based approaches require long training periods before the system can be used. Furthermore, situations are commonly recognised at a low-level of granularity, which limits the scope of situation-aware applications. This paper presents a novel approach to situation determination that attempts to overcome these issues by providing a reusable library of general situation specifications that can be easily extended to create new specific situations, and immediately deployed without the need of an environment expert. A proposed architecture of an accompanying situation determination middleware is provided, as well as an analysis of a prototype implementation