Adaptive Software Fault Prediction Approach Using Object-Oriented Metrics

As users continually request additional functionality, software systems will continue to grow in their complexity, as well as in their susceptibility to failures. Particularly for sensitive systems requiring higher levels of reliability, faulty system modules may increase development and maintenance cost. Hence, identifying them early would support the development of reliable systems through improved scheduling and quality control. Research effort to predict software modules likely to contain faults, as a consequence, has been substantial. Although a wide range of fault prediction models have been proposed, we remain far from having reliable tools that can be widely applied to real industrial systems. For projects with known fault histories, numerous research studies show that statistical models can provide reasonable estimates at predicting faulty modules using software metrics. However, as context-specific metrics differ from project to project, the task of predicting across projects is difficult to achieve. Prediction models obtained from one project experience are ineffective in their ability to predict fault-prone modules when applied to other projects. Hence, taking full benefit of the existing work in software development community has been substantially limited. As a step towards solving this problem, in this dissertation we propose a fault prediction approach that exploits existing prediction models, adapting them to improve their ability to predict faulty system modules across different software projects.

Entrepreneurship in project management systems: proposal of a model and preliminary empirical evidence

This study analyzes the manifestation of the dimensions of Entrepreneurial Orientation (EO) and Project Management Systems (PMS). We used a qualitative approach to conduct exploratory research through a study in literature and a pilot case in a software company. Data was collected from semi structured interviews, documents, and records on file, then triangulated and treated with content analysis. The model proposed for the relationship between the types of PMS (ad hoc, Classic PM, innovation, entrepreneurship/intrapreneurship) and the dimensions of EO (innovativeness, risk-taking, proactiveness, competitive aggressiveness, and autonomy), was partially corroborated by empirical studies. New studies are suggested to validate the applicability and setup of the model.

Free software and free culture in Higher Education: pipelines and workflows for creative purposes

OpenLab ESEV is a project of the School of Education of the Polytechnic Institute of Viseu (ESEV), Portugal, that aims to promote, foster and support the use of Free/Libre Software and Open Source Software, Open Educational Resources, Free Culture, Free file formats and more flexible copyright licenses for creative and educational purposes in the ESEV's domains of activity (education, arts, media). Most of the OpenLab ESEV activities are related to the teacher education and arts and multimedia programs, with a special focus on the later. In this paper, the project and some activities are presented, starting with its origins and its conceptual framework. The presented overview is intended as background for the examination of the use of Free/Libre Software and Free Culture in educational settings, specially at the higher education level, and for creative purposes. The activities developed with students and professionals generated pipelines and workflows implemented for different creative purposes, software packages used for different tasks, choices for file formats and copyright licenses. Finished and ongoing multimedia and arts projects will be presented as real case scenarios.

Effectiveness of non-pharmacological interventions to prevent falls in older people: a systematic overview. The SENATOR Project ONTOP Series

Background: Falls are common events in older people, which cause considerable morbidity and mortality. Non-pharmacological interventions are an important approach to prevent falls. There are a large number of systematic reviews of non-pharmacological interventions, whose evidence needs to be synthesized in order to facilitate evidence-based clinical decision making. Objectives: To systematically examine reviews and meta-analyses that evaluated non-pharmacological interventions to prevent falls in older adults in the community, care facilities and hospitals. Methods: We searched the electronic databases Pubmed, the Cochrane Database of Systematic Reviews, EMBASE, CINAHL, PsycINFO, PEDRO and TRIP from January 2009 to March 2015, for systematic reviews that included at least one comparative study, evaluating any non-pharmacological intervention, to prevent falls amongst older adults. The quality of the reviews was assessed using AMSTAR and ProFaNE taxonomy was used to organize the interventions. Results: Fifty-nine systematic reviews were identified which consisted of single, multiple and multi-factorial non-pharmacological interventions to prevent falls in older people. The most frequent ProFaNE defined interventions were exercises either alone or combined with other interventions, followed by environment/assistive technology interventions comprising environmental modifications, assistive and protective aids, staff education and vision assessment/correction. Knowledge was the third principle class of interventions as patient education. Exercise and multifactorial interventions were the most effective treatments to reduce falls in older adults, although not all types of exercise were equally effective in all subjects and in all settings. Effective exercise programs combined balance and strength training. Reviews with a higher AMSTAR score were more likely to contain more primary studies, to be updated and to perform meta-analysis. Conclusions: The aim of this overview of reviews of non-pharmacological interventions to prevent falls in older people in different settings, is to support clinicians and other healthcare workers with clinical decision-making by providing a comprehensive perspective of findings.

Using digital devices in a first year classroom : a focus on the design and use of phonics software applications

When integrated within a holistic literacy program, phonics applications can be used in classrooms to facilitate students’ self-directed learning of letter-sound knowledge; but are they designed to allow for such a purpose? With most phonics software applications making heavy use of image cues, this project has more specifically investigated whether the design of the images used in such applications may impact on the effectiveness of their self-directed use in classrooms. Using a quasi-experimental study, we compared two types of pictorial mnemonics used in tablet applications, along with teacher-led activity in three first-year classrooms from the one school. The difference between teacher-led activity and integrated picture cues was significant, with teacher-led activity proving more effective. The difference between teacher-led activity and form-taking picture cues, however, was not statistically significant. Given that the outcomes of this small-scale study suggest that image design may be a significant design feature contributing to the educational value of using phonics applications in the classroom, we recommend that the design features of phonics software applications attract further research.

Data, Software, and Advanced Computational Usage of University of Washington Research Leaders

Scientific research is increasingly data-intensive, relying more and more upon advanced computational resources to be able to answer the questions most pressing to our society at large. This report presents findings from a brief descriptive survey sent to a sample of 342 leading researchers at the University of Washington (UW), Seattle, Washington in 2010 and 2011 as the first stage of the larger National Science Foundation project “Interacting with Cyberinfrastructure in the Face of Changing Science.” This survey assesses these researcher’s use of advanced computational resources, data, and software in their research. We present high-level findings that describe UW researchers’: demographics, interdisciplinarity, research groups, data use, software and computational use—including software development and use, data storage and transfer activities, and collaboration tools, and computing resources. These findings offer insights into the state of computational resources in use during this time period as well as offering a look at the data intensiveness of UW researchers.