Gernot Armin Liebchen

• PhD
• Lecturer at Bournemouth University

Web-based portals enable a new communication paradigm that could provide variety of benefits and support to both the customers and companies. Customers can have continuous access to the services, information, support, and payments on the portal with the possibility of personalisation. This paper presents a survey on the usability and user experienc...

Web-based portals enable a new communication paradigm that could provide a variety of benefits and support to both customers and companies. Customers can have continuous access to the services, information, support, and payments on the portal with the possibility of personalisation. This paper presents a survey on the usability and user experience...

Open community web portals and information-sharing platforms have been widely used to generate and share knowledge. Recent advances in technology and growing interest in crowdsourcing tools have helped to improve the technical competency and quality of these platforms. However, usability and user experience aspects are still challenging as satisfyi...

Developing high quality, reliable and on time software systems is challenging due to the increasing size and complexity of these systems. Traditional software development approaches are not suitable for dealing with such challenges, so several approaches have been introduced to increase the productivity and reusability during the software developme...

BACKGROUND Increasing pressure from governments, public health bodies, and consumers is driving a need for increased food-based information provision in eating-out situations. Meals eaten outside the home are known to be less healthy than meals eaten at home, and consumers can complain of poor information on the health impact and allergen content o...

Background: Increasing pressure from governments, public health bodies, and consumers is driving a need for increased food-based information provision in eating-out situations. Meals eaten outside the home are known to be less healthy than meals eaten at home, and consumers can complain of poor information on the health impact and allergen content...

Context: We revisit our review of data quality within the context of empirical software engineering eight years on from our PROMISE 2008 article. Objective: To assess the extent and types of techniques used to manage quality within data sets. We consider this a particularly interesting question in the context of initiatives to promote sharing and s...

Data quality is an important issue which has been addressed and recognised in research communities such as data warehousing, data mining and information systems. It has been agreed that poor data quality will impact the quality of results of analyses and that it will therefore impact on decisions made on the basis of these results. Empirical softwa...

Software products can only be improved if we have a good understanding of the faults they typically contain. Code faults are a significant source of software product problems which we currently do not understand sufficiently. Open source change repositories are potentially a rich and valuable source of fault data for both researchers and practition...

OBJECTIVE - to assess the extent and types of techniques used to manage quality within software engineering data sets. We consider this a particularly interesting question in the context of initiatives to promote sharing and secondary analysis of data sets. METHOD - we perform a systematic review of available empirical software engineering studies....

Data quality is an important aspect of empirical analysis. This paper compares three noise handling methods to assess the benefit of identifying and either filtering or editing problematic instances. We compare a 'do nothing' strategy with (i) filtering, (ii) robust filtering and (Hi) filtering followed by polishing. A problem is that it is not pos...

OBJECTIVE -The aim is to report upon an assessment of the impact noise has on the predictive accuracy by comparing noise handling techniques. METHOD -We describe the process of cleaning a large software management dataset comprising initially of more than 10,000 projects. The data quality is mainly assessed through feedback from the data provider a...

An attempt is made to address the problem of classifying incomplete software project data. The essence of the approach is the proposal that software effort can be predicted in probabilistic terms given incomplete software project data using decision trees. This approach is based on the a priori probability of each value determined from the instance...

The paper reports on an ongoing investigation into software productivity and its influencing factors. Analysis of a data set containing project management of a large multinational company. The data set contains tables holding information about more than 25000 closed projects collected since 1990. Due to incomplete data only 1413 closed projects cou...