Traceability ensures that software artifacts of subsequent phases of the development cycle are consistent. Few works have so far addressed the problem of automatically recovering traceability links between object-oriented (OO) design and code entities. Such a recovery process is required whenever there is no explicit support of traceability from the development process. The recovered information can drive the evolution of the available design so that it corresponds to the code, thus providing a still useful and updated high-level view of the system.
Automatic recovery of traceability links can be achieved by determining the similarity of paired elements from design and code. The choice of the properties involved in the similarity computation is crucial for the success of the recovery process. In fact, design and code objects are complex artifacts with several properties attached. The basic anchors of the recovered traceability links should be chosen as those properties (or property combinations) which are expected to be maintained during the transformation of design into code. This may depend on specific practices and/or the development environment, which should therefore be properly accounted for.
In this paper different categories of basic properties of design and code entities will be analyzed with respect to the contribution they give to traceability recovery. Several industrial software components will be employed as a benchmark on which the performances of the alternatives are measured. 相似文献
Companies are beginning to expect to gain strategic value from the implementation and operation of enterprise systems (ES). Currently dominating trends in business are sense-and-respond business models, globalization, corporate realignment, virtual organizations and accelerated product life-cycles. Available and evolving features of enterprise systems are summarized in a framework, concluding that present capabilities of enterprise systems correspond only to some extend to the new practices required to respond to these corporate challenges, and that ERP vendors strive to fill the gap. By integrating higher management functions enterprise systems will also impact on the practice of executives. The future work of an executive is illustrated by a fictitious example. 相似文献
This article proposes a compact algorithm for optimisation in noisy environments. This algorithm has a compact structure and employs differential evolution search logic. Since it is a compact algorithm, it does not store a population of solutions but a probabilistic representation of the population. This kind of algorithmic structure can be implemented in those real-world problems characterized by memory limitations. The degree of randomization contained in the compact structure allows a robust behaviour in the presence of noise. In addition the proposed algorithm employs the noise analysis survivor selection scheme. This scheme performs an analysis of the noise and automatically performs a re-sampling of the solutions in order to ensure both reliable pairwise comparisons and a minimal cost in terms of fitness evaluations. The noise analysis component can be reliably used in noise environments affected by Gaussian noise which allow an a priori analysis of the noise features. This situation is typical of problems where the fitness is computed by means of measurement devices. An extensive comparative analysis including four different noise levels has been included. Numerical results show that the proposed algorithm displays a very good performance since it regularly succeeds at handling diverse fitness landscapes characterized by diverse noise amplitudes. 相似文献
In the past decade, support vector machines (SVMs) have gained the attention of many researchers. SVMs are non-parametric supervised learning schemes that rely on statistical learning theory which enables learning machines to generalize well to unseen data. SVMs refer to kernel-based methods that have been introduced as a robust approach to classification and regression problems, lately has handled nonlinear identification problems, the so called support vector regression. In SVMs designs for nonlinear identification, a nonlinear model is represented by an expansion in terms of nonlinear mappings of the model input. The nonlinear mappings define a feature space, which may have infinite dimension. In this context, a relevant identification approach is the least squares support vector machines (LS-SVMs). Compared to the other identification method, LS-SVMs possess prominent advantages: its generalization performance (i.e. error rates on test sets) either matches or is significantly better than that of the competing methods, and more importantly, the performance does not depend on the dimensionality of the input data. Consider a constrained optimization problem of quadratic programing with a regularized cost function, the training process of LS-SVM involves the selection of kernel parameters and the regularization parameter of the objective function. A good choice of these parameters is crucial for the performance of the estimator. In this paper, the LS-SVMs design proposed is the combination of LS-SVM and a new chaotic differential evolution optimization approach based on Ikeda map (CDEK). The CDEK is adopted in tuning of regularization parameter and the radial basis function bandwith. Simulations using LS-SVMs on NARX (Nonlinear AutoRegressive with eXogenous inputs) for the identification of a thermal process show the effectiveness and practicality of the proposed CDEK algorithm when compared with the classical DE approach. 相似文献
Solving reliability-redundancy optimization problems via meta-heuristic algorithms has attracted increasing attention in recent years. In this paper, an effective coevolutionary differential evolution with harmony search algorithm (CDEHS) is proposed to solve the reliability-redundancy optimization problem by dividing the problem into a continuous part and an integer part. In CDEHS, two populations evolve simultaneously and cooperatively, where one population for the continuous part evolves by means of differential evolution while another population for the integer part evolves by means of harmony search. After half of the whole evolving process, the integer part stops evolving and provides the best solution to the other part for further evolving with differential evolution. Simulations results based on three typical problems and comparisons with some existing algorithms show that the proposed CDEHS is effective, efficient and robust for solving the reliability-redundancy optimization problem. 相似文献
Sexual selection and mating systems profoundly influence the behavior and psychology of animals. Using their own studies of green anacondas (Eunectes murinus) and reviewing other recent studies, the authors conclude that incomplete data derived from a few well-studied snake species have led to general acceptance of polygyny as the dominant mating system in snakes. New data on behavior, paternity, and life history in a diverse taxonomic array of snakes support the view that polyandry is not only common in snakes but may have been the ancestral mating system. This interpretation helps to explain many seemingly paradoxical behavioral differences between lizards and snakes, such as the lack of territorial systems in most snakes and their frequent female-biased sexual size dimorphism. (PsycINFO Database Record (c) 2010 APA, all rights reserved) 相似文献