Naming the Pain in Requirements Engineering: A Design for a Global Family of Surveys and First Results from Germany

For many years, we have observed industry struggling in defining a high quality requirements engineering (RE) and researchers trying to understand industrial expectations and problems. Although we are investigating the discipline with a plethora of empirical studies, they still do not allow for empirical generalisations. To lay an empirical and externally valid foundation about the state of the practice in RE, we aim at a series of open and reproducible surveys that allow us to steer future research in a problem-driven manner. We designed a globally distributed family of surveys in joint collaborations with different researchers and completed the first run in Germany. The instrument is based on a theory in the form of a set of hypotheses inferred from our experiences and available studies. We test each hypothesis in our theory and identify further candidates to extend the theory by correlation and Grounded Theory analysis. In this article, we report on the design of the family of surveys, its underlying theory, and the full results obtained from Germany with participants from 58 companies. The results reveal, for example, a tendency to improve RE via internally defined qualitative methods rather than relying on normative approaches like CMMI. We also discovered various RE problems that are statistically significant in practice. For instance, we could corroborate communication flaws or moving targets as problems in practice. Our results are not yet fully representative but already give first insights into current practices and problems in RE, and they allow us to draw lessons learnt for future replications. Our results obtained from this first run in Germany make us confident that the survey design and instrument are well-suited to be replicated and, thereby, to create a generalisable empirical basis of RE in practice

Mad spaces

Paper presented at COMMON-PLACE Seminar, The Lighthouse, Glasgo

In Defence of Modest Doxasticism About Delusions

Here I reply to the main points raised by the commentators on the arguments put forward in my Delusions and Other Irrational Beliefs (OUP, 2009). My response is aimed at defending a modest doxastic account of clinical delusions, and is articulated in three sections. First, I consider the view that delusions are in-between perceptual and doxastic states, defended by Jacob Hohwy and Vivek Rajan, and the view that delusions are failed attempts at believing or not-quite-beliefs, proposed by Eric Schwitzgebel and Maura Tumulty. Then, I address the relationship between the doxastic account of delusions and the role, nature, and prospects of folk psychology, which is discussed by Dominic Murphy, Keith Frankish, and Maura Tumulty in their contributions. In the final remarks, I turn to the continuity thesis and suggest that, although there are important differences between clinical delusions and non-pathological beliefs, these differences cannot be characterised satisfactorily in epistemic terms. \u

Non-linear Causal Inference using Gaussianity Measures

We provide theoretical and empirical evidence for a type of asymmetry between causes and effects that is present when these are related via linear models contaminated with additive non-Gaussian noise. Assuming that the causes and the effects have the same distribution, we show that the distribution of the residuals of a linear fit in the anti-causal direction is closer to a Gaussian than the distribution of the residuals in the causal direction. This Gaussianization effect is characterized by reduction of the magnitude of the high-order cumulants and by an increment of the differential entropy of the residuals. The problem of non-linear causal inference is addressed by performing an embedding in an expanded feature space, in which the relation between causes and effects can be assumed to be linear. The effectiveness of a method to discriminate between causes and effects based on this type of asymmetry is illustrated in a variety of experiments using different measures of Gaussianity. The proposed method is shown to be competitive with state-of-the-art techniques for causal inference.Comment: 35 pages, 9 figure

An experience of teacher education on task design in Colombia

We describe an experience in task design within an in-service secondary mathematics teacher education program in Colombia. Following a model known as didactic analysis, a team of researchers, educators, mentors and practicing teachers worked together in designing, implementing, assessing and reformulating secondary school mathematics tasks. We present here the main features of the framework on which the program is based, identify some of the characteristics of the experience lived by trainees, educators and researchers on task design during the first implementation of the program, and analyse the trainees’ assessment on their own proposals of tasks and on the contribution of the program on their task design competencies