A quantitative analysis of the unit verification perspective on fault distributions in complex software systems: an operational replication

Unit verification, including software inspections and unit tests, is usually the first code verification phase in the software development process. However, principles of unit verification are weakly explored, mostly due to the lack of data, since unit verification data are rarely systematically collected and only a few studies have been published with such data from industry. Therefore, we explore the theory of fault distributions, originating in the quantitative analysis by Fenton and Ohlsson, in the weakly explored context of unit verification in large-scale software development. We conduct a quantitative case study on a sequence of four development projects on consecutive releases of the same complex software product line system for telecommunication exchanges. We replicate the operationalization from earlier studies, analyzed hypotheses related to the Pareto principle of fault distribution, persistence of faults, effects of module size, and quality in terms of fault densities, however, now from the perspective of unit verification. The patterns in unit verification results resemble those of later verification phases, e.g., regarding the Pareto principle, and may thus be used for prediction and planning purposes. Using unit verification results as predictors may improve the quality and efficiency of software verification.     

Shakedown analysis of circular plates using a yield criterion of the mean

Structural optimization based on the shakedown theory is a powerful and promising technique. However, due to the nonlinearities of physical materials and the number of variable loads in real structures, it is computationally complex and time-consuming. To simplify the occurring non-linear, non-convex optimization problems, the paper suggests reducing the number of yield conditions. The so-called a yield criterion of the mean (integral yield condition) is analysed and explained in detail, which allows taking into account one yield condition for the entire finite element instead of multiple point-wise conditions. This approach shows promising results in numerical application to the optimization of a circular plate, considering a possibility of employing the yield criteria of the mean or pointwise yield conditions in different areas of the plate in particular. The methods applied are based on the assumptions of perfect plasticity and small deformations.     

A novel fuzzy multi-criteria decision framework for sustainable supplier selection with incomplete information

Both academic and corporate interest in sustainable supply chains has increased in recent years. Supplier selection process is one of the key operational tasks for sustainable supply chain management. This paper examines the problem of identifying an effective model based on sustainability principles for supplier selection operations in supply chains. Due to its multi-criteria nature, the sustainable supplier evaluation process requires an appropriate multi-criteria analysis and solution approach. The approach should also consider that decision makers might face situations such as time pressure, lack of expertise in related issue, etc., during the evaluation process. The paper develops a novel approach based on fuzzy analytic network process within multi-person decision-making schema under incomplete preference relations. The method not only makes sufficient evaluations using the provided preference information, but also maintains the consistency level of the evaluations. Finally, the paper analyzes the sustainability of a number of suppliers in a real-life problem to demonstrate the validity of the proposed evaluation model.     

From insect to Internet: Situated control for networked robot teams

Ant-like systems take advantage of agents' situatedness to reduce or eliminate the need for centralized control or global knowledge. This reduces the need for complexity of individuals and leads to robust, scalable systems. Such insect-inspired situated approaches have proven effective both for task performance and task allocation. The desire for general, principled techniques for situated interaction has led us to study the exploitation of abstract situatedness – situatedness in non-physical environments. The port-arbitrated behavior-based control approach provides a well-structured abstract behavior space in which agents can participate in situated interaction. We focus on the problem of role assumption, distributed task allocation in which each agent selects its own task-performing role. This paper details our general, principled Broadcast of Local Eligibility (BLE) technique for role-assumption in such behavior-space-situated systems, and provides experimental results from the CMOMMT target-tracking task. This revised version was published online in August 2006 with corrections to the Cover Date.     

Slow and fast diffusion effects in image processing

A mathematical model for a nonlinear image multiscale analysis is studied. Processing of an image is based on a solution of the strongly nonlinear parabolic partial differential equation, which can degenerate depending on values of the greylevel intensity function. The governing PDE is a generalization of the regularized (in the sense of Catté, Lions, Morel and Coll) Perona-Malik anisotropic diffusion equation. We present numerical techniques for solving the suggested initial-boundary value problem and also existence and convergence results. Numerical experiments are discussed. Received: 6 May 1998 / Accepted: 27 July 2000     

Interactive visual steering--rapid visual prototyping of a common rail injection system

Interactive steering with visualization has been a common goal of the visualization research community for twenty years, but it is rarely ever realized in practice. In this paper we describe a successful realization of a tightly coupled steering loop, integrating new simulation technology and interactive visual analysis in a prototyping environment for automotive industry system design. Due to increasing pressure on car manufacturers to meet new emission regulations, to improve efficiency, and to reduce noise, both simulation and visualization are pushed to their limits. Automotive system components, such as the powertrain system or the injection system have an increasing number of parameters, and new design approaches are required. It is no longer possible to optimize such a system solely based on experience or forward optimization. By coupling interactive visualization with the simulation back-end (computational steering), it is now possible to quickly prototype a new system, starting from a non-optimized initial prototype and the corresponding simulation model. The prototyping continues through the refinement of the simulation model, of the simulation parameters and through trial-and-error attempts to an optimized solution. The ability to early see the first results from a multidimensional simulation space--thousands of simulations are run for a multidimensional variety of input parameters--and to quickly go back into the simulation and request more runs in particular parameter regions of interest significantly improves the prototyping process and provides a deeper understanding of the system behavior. The excellent results which we achieved for the common rail injection system strongly suggest that our approach has a great potential of being generalized to other, similar scenarios.     

Morphometric and some immunohistochemical characteristics of human choroids plexus stroma and psammoma bodies

Psammoma bodies (PBs) are one of many choroids plexus aging changes. The aim of our research was to perform the quantification of PBs' presence in human choroids plexus stroma, as well as to evaluate the characteristics of choroids plexus stroma in cases in which PBs were present. Afterwards, the observations of the histochemical analysis would be confirmed by immunohistochemical analysis. Choroid plexuses of 30 cadavers were used for the histochemical and, choroids plexuses of 15 cadavers in which PBs' presence was confirmed during the histochemical analysis, were used as material for the immunohistochemical analysis. Light microscopy, histochemical, immunohistochemical, and morphometric method were applied during the study. Classification of the cases was performed by cluster analysis. We observed increase of choroids plexus PBs' presence during the aging process. But this increase is not linear. Their presence is the largest in the second cluster that is younger than the third and older than the first. Nuclear morphometric parameters of the stroma in these cases showed that the cellular composition in this cluster is different than in other two and, that contain larger number of lymphoid cells. Immunohistochemical analysis showed PBs' positive reaction on vimentin, CD45R0, and LCA markers, while in their vicinity, as well as inside them, numerous T-cells were observed. So, the presence of CD45R0 and LCA-positive T cells, PBs' positive reaction on the same markers, indirectly connect these cells with PBs' formation process.     

On the Convergence of Temporal-Difference Learning with Linear Function Approximation

The asymptotic properties of temporal-difference learning algorithms with linear function approximation are analyzed in this paper. The analysis is carried out in the context of the approximation of a discounted cost-to-go function associated with an uncontrolled Markov chain with an uncountable finite-dimensional state-space. Under mild conditions, the almost sure convergence of temporal-difference learning algorithms with linear function approximation is established and an upper bound for their asymptotic approximation error is determined. The obtained results are a generalization and extension of the existing results related to the asymptotic behavior of temporal-difference learning. Moreover, they cover cases to which the existing results cannot be applied, while the adopted assumptions seem to be the weakest possible under which the almost sure convergence of temporal-difference learning algorithms is still possible to be demonstrated.     

Kernel least-squares models using updates of the pseudoinverse

Sparse nonlinear classification and regression models in reproducing kernel Hilbert spaces (RKHSs) are considered. The use of Mercer kernels and the square loss function gives rise to an overdetermined linear least-squares problem in the corresponding RKHS. When we apply a greedy forward selection scheme, the least-squares problem may be solved by an order-recursive update of the pseudoinverse in each iteration step. The computational time is linear with respect to the number of the selected training samples.