Determining the quality of mathematical software using reference data sets

This paper describes a methodology for evaluating the numerical accuracy of software that performs mathematical calculations. The authors explain how this methodology extends the concept of metrological traceability, which is fundamental to measurement, to include software quality. Overviews of two European Union-funded projects are also presented. The first project developed an infrastructure to allow software to be verified by testing, via the internet, using reference data sets. The primary focus of the project was software used within systems that make physical measurements. The second project, currently underway, explores using this infrastructure to verify mathematical software used within general scientific and engineering disciplines. Publications on using reference data sets for the verification of mathematical software are usually intended for a readership specialising in measurement science or mathematics. This paper is aimed at a more general readership, in particular software quality specialists and computer scientists. Further engagement with experts in these disciplines will be helpful to the continued development of this application of software quality

Cognitive Complexity Measures: An Analysis

Cognitive informatics (CI), a multidisciplinary area of research tries to solve the common problems in the field of informatics, computer science, software engineering, mathematics, cognitive science, neurobiology, psychology, and physiology. Measurement in software engineering is also a core issue which is still striving for its standardization process. In recent years, several cognitive complexity measures based on CI have been proposed. However, each of them has their own advantages and disadvantages. This chapter presents a critical review on existing cognitive complexity measures. Furthermore, a comparative study based on some selected attributes has been presented

Learning about assistive technology from high school

[Abstract] This communication will present an educative and research project that has linked the creation of 3D Assistive Technology (AT) for people with disabilities with the training of students of secondary education. STEMBach educational program aims to provide quality scientific education to secondary school students in the fields of science, technology, engineering, and mathematics (STEM) through research projects. Specifically, the text focuses on one project proposed by the TALIONIS research group, which uses 3D printers to design and create assistive technology (AT) for people with disabilities. The project involves students from eight different high schools and ten individuals with disabilities from four non-governmental organizations. The students design and print the AT using software such as Tinkercad and Cura Software. After testing the AT, outcome measurement instruments are used to validate their effectiveness. The project is based on a Learning-by-doing methodology with a structure of service-learning, and the involvement of the students is voluntary. The objectives of the project are to involve the students in research and innovation, to generate resources and AT for people with disabilities, and to determine the effects of AT on the lives of its users. Finally, the project leads to identifying new needs of people with disabilities that could be addressed through further research work

An Analysis of Publication Venues for Automatic Differentiation Research

We present the results of our analysis of publication venues for papers on automatic differentiation (AD), covering academic journals and conference proceedings. Our data are collected from the AD publications database maintained by the autodiff.org community website. The database is purpose-built for the AD field and is expanding via submissions by AD researchers. Therefore, it provides a relatively noise-free list of publications relating to the field. However, it does include noise in the form of variant spellings of journal and conference names. We handle this by manually correcting and merging these variants under the official names of corresponding venues. We also share the raw data we get after these corrections.Comment: 6 pages, 3 figure

Innovation, skills and performance in the downturn: an analysis of the UK innovation survey 2011

The link between firms’ innovation performance and economic cycles, especially major downturns such as that of 2008-10, is a matter of great policy significance, but is relatively under-researched at least at the level of micro data on business behaviour. It is, for example, often argued that economies need to ‘innovate out of recessions’ since innovation is positively associated with improvements in productivity that then lead to growth and better employment (Nesta, 2009). The issues of how individual firms respond to downturns through their investment in innovation, and how this impacts on innovation outputs and ultimately business performance and growth during and after downturns, has been less studied because relevant data has not been readily available. The UK Innovation Survey (UKIS) 2011 now makes this possible. The UKIS 2011 with reference period 2008 to 2010 covers the downturn in economic activity generated by the global financial crash. The build-up of panels over the life of the UKIS also supports analysis of the longer-term interactions between innovation and the business cycle. This report analyses the last four waves of the surveys. Further, the latest survey includes questions on whether firms employ a specific set of skills, which adds materially to the ability to research the role of skills and human capital in innovation at the micro level

Evaluation of software dependability

It has been said that the term software engineering is an aspiration not a description. We would like to be able to claim that we engineer software, in the same sense that we engineer an aero-engine, but most of us would agree that this is not currently an accurate description of our activities. My suspicion is that it never will be. From the point of view of this essay – i.e. dependability evaluation – a major difference between software and other engineering artefacts is that the former is pure design. Its unreliability is always the result of design faults, which in turn arise as a result of human intellectual failures. The unreliability of hardware systems, on the other hand, has tended until recently to be dominated by random physical failures of components – the consequences of the ‘perversity of nature’. Reliability theories have been developed over the years which have successfully allowed systems to be built to high reliability requirements, and the final system reliability to be evaluated accurately. Even for pure hardware systems, without software, however, the very success of these theories has more recently highlighted the importance of design faults in determining the overall reliability of the final product. The conventional hardware reliability theory does not address this problem at all. In the case of software, there is no physical source of failures, and so none of the reliability theory developed for hardware is relevant. We need new theories that will allow us to achieve required dependability levels, and to evaluate the actual dependability that has been achieved, when the sources of the faults that ultimately result in failure are human intellectual failures