Verifying Web Applications: From Business Level Specifications to Automated Model-Based Testing

One of reasons preventing a wider uptake of model-based testing in the industry is the difficulty which is encountered by developers when trying to think in terms of properties rather than linear specifications. A disparity has traditionally been perceived between the language spoken by customers who specify the system and the language required to construct models of that system. The dynamic nature of the specifications for commercial systems further aggravates this problem in that models would need to be rechecked after every specification change. In this paper, we propose an approach for converting specifications written in the commonly-used quasi-natural language Gherkin into models for use with a model-based testing tool. We have instantiated this approach using QuickCheck and demonstrate its applicability via a case study on the eHealth system, the national health portal for Maltese residents.Comment: In Proceedings MBT 2014, arXiv:1403.704

Estimating continuous-time income models

While earning processes are commonly unobservable income flows which evolve in continuous time, observable income data are usually discrete, having been aggregated over time. We consider continuous-time earning processes, specifically (non-linearly) transformed Ornstein-Uhlenbeck processes, and the associated integrated, i.e. time aggregated process. Both processes are characterised, and we show that time aggregation alters important statistical properties. The parameters of the earning process are estimable by GMM, and the finite sample properties of the estimator are investigated. Our methods are applied to annual earnings data for the US. It is demonstrated that the model replicates well important features of the earnings distribution. Keywords; integrated non-linearly transformed ornstein-uhlenbeck process, temporal aggregation

Weak convergence to the t-distribution

We present a new limit theorem for random means: if the sample size is not deterministic but has a negative binomial or geometric distribution, the limit distribution of the normalised random mean is a t-distribution with degrees of freedom depending on the shape parameter of the negative binomial distribution. Thus the limit distribution exhibits exhibits heavy tails, whereas limit laws for random sums do not achieve this unless the summands have innite variance. The limit law may help explain several empirical regularities. We consider two such examples: rst, a simple model is used to explain why city size growth rates are approximately t-distributed. Second, a random averaging argument can account for the heavy tails of high-frequency returns. Our empirical investigations demonstrate that these predictions are borne out by the data.convergence, t-distribution, limit theorem

Patents, Entrepreneurship and Performance

This paper provides an overview of a new database that uses intellectual property data to track the innovative activity of firms in the UK. The paper looks at the extent and nature of patenting activity, focusing on micro firms and SMEs. Over the period 2000 to 2007, SME patenting has increased whereas large firm patenting has fallen and micro firm patenting has been roughly con- stant. Most micro and SMEs patent while relatively young (aged ten or less) and this tendency is becoming more pronounced over time. The paper provides a descriptive analysis on micro firms and SMEs that become high growth firms (defined as having greater than 20 percent growth per annum). Overall, 28.0 percent of young micro and SMEs achieve high growth (over 2002 to 2007). In comparison, 29.4 percent of young micro or SMEs that patent achieve high growth. This difference is much greater for firms in the high-tech industries. Moreover, the analysis shows that due to the skewed nature of the firm-level growth distribution, standard conditional mean estimators may fail to uncover important differences in the association between patenting and firm growth across the conditional growth distribution.Firm growth, patents

Evolution of star clusters in arbitrary tidal fields

We present a novel and flexible tensor approach to computing the effect of a time-dependent tidal field acting on a stellar system. The tidal forces are recovered from the tensor by polynomial interpolation in time. The method has been implemented in a direct-summation stellar dynamics integrator (NBODY6) and test-proved through a set of reference calculations: heating, dissolution time and structural evolution of model star clusters are all recovered accurately. The tensor method is applicable to arbitrary configurations, including the important situation where the background potential is a strong function of time. This opens up new perspectives in stellar population studies reaching to the formation epoch of the host galaxy or galaxy cluster, as well as for star-burst events taking place during the merger of large galaxies. A pilot application to a star cluster in the merging galaxies NGC 4038/39 (the Antennae) is presented.Comment: 12 pages, 8 figures. Accepted for publication in MNRA