Potential Errors and Test Assessment in Software Product Line Engineering

Software product lines (SPL) are a method for the development of variant-rich software systems. Compared to non-variable systems, testing SPLs is extensive due to an increasingly amount of possible products. Different approaches exist for testing SPLs, but there is less research for assessing the quality of these tests by means of error detection capability. Such test assessment is based on error injection into correct version of the system under test. However to our knowledge, potential errors in SPL engineering have never been systematically identified before. This article presents an overview over existing paradigms for specifying software product lines and the errors that can occur during the respective specification processes. For assessment of test quality, we leverage mutation testing techniques to SPL engineering and implement the identified errors as mutation operators. This allows us to run existing tests against defective products for the purpose of test assessment. From the results, we draw conclusions about the error-proneness of the surveyed SPL design paradigms and how quality of SPL tests can be improved.Comment: In Proceedings MBT 2015, arXiv:1504.0192

Engaging with farmers as entrepreneurs and partners: experiences with a self-assessment tool for farmer'organisations (FORCE)

Governments, donors and companies increasingly perceive small farmers and their organisations as development actors and business partners. A practical self-assessment tool, 'Farmers Organizations Reviewing Capacities and Entrepreneurship' (FORCE), takes up the challenge to translate the recognition of farmers' agency into operational practices. we demonstrate that FORCE is an effective tool to quickly map how farmers perceive their organisation and business relations. Self-assessment results of farmer groups in coastal Kenya illustrate how the tool is applied and how farmers' views are plotted in easily understandable scores and graphs

Marketing relations and communication infrastructure development in the banking sector based on big data mining

Purpose: The article aims to study the methodological tools for applying the technologies of intellectual analysis of big data in the modern digital space, the further implementation of which can become the basis for the marketing relations concept implementation in the banking sector of the Russian Federation‘ economy. Structure/Methodology/Approach: For the marketing relations development in the banking sector in the digital economy, it seems necessary: firstly, to identify the opportunities and advantages of the big data mining in banking marketing; secondly, to identify the sources and methods of processing big data; thirdly, to study the examples of the big data mining successful use by Russian banks and to formulate the recommendations on the big data technologies implementation in the digital marketing banking strategy. Findings: The authors‘ analysis showed that big data technologies processing of open online and offline sources of information significantly increases the data amount available for intelligent analysis, as a result of which the interaction between the bank and the target client reaches a new level of partnership. Practical Implications: Conclusions and generalizations of the study can be applied in the practice of managing financial institutions. The results of the study can be used by bank management to form a digital marketing strategy for long-term communication. Originality/Value: The main contribution of this study is that the authors have identified the main directions of using big data in relationship marketing to generate additional profit, as well as the possibility of intellectual analysis of the client base, aimed at expanding the market share and retaining customers in the banking sector of the economy.peer-reviewe

Bridging the Innovation Divide: An Agenda for Disseminating Technology Innovations within the Nonprofit Sector

Examines technology practices -- such as neighborhood information systems, electronic advocacy, Internet-based micro enterprise support, and digital inclusion initiatives -- that strengthen the capacity of nonprofits and community organizations

Product Focused Freeform Fabrication Education

Presented in this paper is our experience of teaching freeform fabrication to students at the Missouri University of Science and Technology, and to high school students and teachers. The emphasis of the curriculum is exposing students to rapid product development technologies with the goal of creating awareness to emerging career opportunities in CAD/CAM. Starting from solid modeling, principles of freeform fabrication, to applications of rapid prototyping and manufacturing in industry sponsored product development projects, students can learn in-depth freeform fabrication technologies. Interactive course content with hands-on experience for product development is the key towards the success of the program.Mechanical Engineerin

Management Quality Measurement: Using Data Envelopment Analysis (DEA) Estimation Approach for Banks in Brazil

While the quality of a bank's management is generally acknowledged to be a key contributor to a financial institutional failure, it is usually not calculated for lack of an objective measure. This paper presents a new paradigm approach for quantifying a bank's managerial efficiency, using a data envelopment analysis (DEA) model that combines multiple inputs and outputs to compute a scalar measure of efficiency and management quality. The analysis of the largest 50 Brazilian banks over a twelve-year period from 1995 to 2006 shows significant differences in management quality scores between institutions. Hence, this new metric provides an important, but previously missing, modelling element for the early identification of troubled banks and can be used as a tool for off-site bank supervision in Brazil.Data Envelopment Analysis, DEA, Banks, Brazil

Dynamic real-time risk analytics of uncontrollable states in complex internet of things systems, cyber risk at the edge

The Internet of Things (IoT) triggers new types of cyber risks. Therefore, the integration of new IoT devices and services requires a self-assessment of IoT cyber security posture. By security posture this article refers to the cybersecurity strength of an organisation to predict, prevent and respond to cyberthreats. At present, there is a gap in the state of the art, because there are no self-assessment methods for quantifying IoT cyber risk posture. To address this gap, an empirical analysis is performed of 12 cyber risk assessment approaches. The results and the main findings from the analysis is presented as the current and a target risk state for IoT systems, followed by conclusions and recommendations on a transformation roadmap, describing how IoT systems can achieve the target state with a new goal-oriented dependency model. By target state, we refer to the cyber security target that matches the generic security requirements of an organisation. The research paper studies and adapts four alternatives for IoT risk assessment and identifies the goal-oriented dependency modelling as a dominant approach among the risk assessment models studied. The new goal-oriented dependency model in this article enables the assessment of uncontrollable risk states in complex IoT systems and can be used for a quantitative self-assessment of IoT cyber risk posture

Functional Bipartite Ranking: a Wavelet-Based Filtering Approach

It is the main goal of this article to address the bipartite ranking issue from the perspective of functional data analysis (FDA). Given a training set of independent realizations of a (possibly sampled) second-order random function with a (locally) smooth autocorrelation structure and to which a binary label is randomly assigned, the objective is to learn a scoring function s with optimal ROC curve. Based on linear/nonlinear wavelet-based approximations, it is shown how to select compact finite dimensional representations of the input curves adaptively, in order to build accurate ranking rules, using recent advances in the ranking problem for multivariate data with binary feedback. Beyond theoretical considerations, the performance of the learning methods for functional bipartite ranking proposed in this paper are illustrated by numerical experiments

SME Access to Finance: An exploration into the demand and supply contraints around SME access to finance

In March 2011, the Newcastle Business School, Northumbria University was commissioned by North East Access to Finance (NEA2F) to undertake a major piece of independent academic research to explore both the demand and supply sides of SME access to finance in the North East of England. The aim of the research was to gain insight and understanding into the challenges faced not only by the SME sector but also by the key suppliers of finance to that community, specifically the banking sector and Business Angels. Thus we do not take a position on what we think is right or what a best practice approach might be but rather reflect, as accurately as possible, the information that was shared with us. The research project commenced in May 2011 and was completed at the end of March 2012