Applying black-box testing to UML/OCL database models

Most Unified Modeling Language (UML) computer-aided software engineering tools have been insufficient in the development process because they provide little support for conceptual model testing. Model testing aims to ensure the correctness of a UML/OCL class diagram, or, in other words, that a given class diagram can perfectly meet the user’s requirements. This study proposes the validation of class diagrams with black-box testing, a technique used to test software without focusing on the software’s implementation or structure. An approach is proposed for the automatic transformation of the constraints of a UML/OCL class diagram into test cases. Following the creation of the test cases, they are executed with JUnit and the results produced are shown to the tester. To demonstrate the applicability of this approach, an effectiveness evaluation and an efficiency evaluation are performed here. Evaluation studies show that all faults included in a class diagram have been detected within an efficient time.     

MOE prediction in Abies pinsapo Boiss. timber: Application of an artificial neural network using non-destructive testing

Determining the modulus of elasticity of wood by applying an artificial neural network using the physical properties and non-destructive testing can be a useful method in assessments of the timber structure in old constructions. The modulus of elasticity of Abies pinsapo Boiss. timber was predicted in this study through the parameters of density, width, thickness, moisture content, ultrasonic wave propagation velocity and visual grading of the test pieces. A feedforward multilayer perceptron network was designed for this purpose, achieving 75.0% success in the testing or unknown group.     

Reinforcement learning of pedagogical policies in adaptive and intelligent educational systems

In an adaptive and intelligent educational system (AIES), the process of learning pedagogical policies according the students needs fits as a Reinforcement Learning (RL) problem. Previous works have demonstrated that a great amount of experience is needed in order for the system to learn to teach properly, so applying RL to the AIES from scratch is unfeasible. Other works have previously demonstrated in a theoretical way that seeding the AIES with an initial value function learned with simulated students reduce the experience required to learn an accurate pedagogical policy. In this paper we present empirical results demonstrating that a value function learned with simulated students can provide the AIES with a very accurate initial pedagogical policy. The evaluation is based on the interaction of more than 70 Computer Science undergraduate students, and demonstrates that an efficient and useful guide through the contents of the educational system is obtained.     

Visual specification of measurements and redesigns for domain specific visual languages

Ensuring model quality is a key success factor in many computer science areas, and becomes crucial in recent software engineering paradigms like the one proposed by model-driven software development. Tool support for measurements and redesigns becomes essential to help developers improve the quality of their models. However, developing such helper tools for the wide variety of (frequently domain specific) visual notations used by software engineers is a hard and repetitive task that does not take advantage from previous developments, thus being frequently forgotten.In this paper we present our approach for the visual specification of measurements and redesigns for Domain Specific Visual Languages (DSVLs). With this purpose, we introduce a novel DSVL called SLAMMER that contains generalisations of some of the more used types of internal product measurements and redesigns. The goal is to facilitate the task of defining measurements and redesigns for any DSVL, as well as the generation of tools from such specification reducing or eliminating the necessity of coding. We rely on the use of visual patterns for the specification of the relevant elements for each measurement and redesign type. In addition, SLAMMER allows the specification of redesigns either procedurally or by means of graph transformation rules. These redesigns can be triggered when the measurements reach a certain threshold.These concepts have been implemented in the meta-modelling tool AToM³. In this way, when a DSVL is designed, it is possible to specify measurements and redesigns that will become available in the final modelling environment generated for the language. As an example, we show a case study in the web modelling domain.     

Methodological variations in the production of CORINE land cover and consequences for long-term land cover change studies. The case of Spain.

ABSTRACT

Land cover information at national or regional scale is essential for science, monitoring, reporting, and policy making. CORINE Land Cover (CLC) is the most consistent land cover map for the entire European territory, with four repetitions during the period 1985–2012. The long-term consistency of CLC maps is the most appreciated strength and it should be guaranteed. Beyond some common general guidelines, the mapping approaches used in individual countries differ and change over time, leading to inconsistencies that should be known and reported. Through a series of metrics over the Spanish CLC most recent layers (CLC2006 and CLC2012) and comparisons with eight other countries CLC statistics, we demonstrate that the methodological changes recently implemented have introduced some discrepancies with previous CLC versions. The most affected classes in Spain were transitional woodland-shrub, complex cultivation patterns, artificial, grasslands, and forests. Users should be aware of the important implications these discrepancies may have in land use and land cover change studies, trend analysis, and reports.     

Rheological changes during thermal processing of low-fat meat emulsions formulated with different texture-modifying ingredients

The rheological behaviour of high-fat (22%) and low-fat (8%) meat emulsions during thermal processing in the presence (3%) of various texture-modifying non-meat ingredients, namely maltodextrin, starch, wheat flour, egg white and apple fibre, was analysed. Rheological properties of emulsions were assessed using non-destructive measurements (thermal scanning rigidity monitor, TSRM). The lower the fat content, the lower were the rigidity values of meat emulsions throughout the temperature range studied. Emulsions made with maltodextrin proved less rigid. Addition of starch and egg white favoured the formation of more rigid structures in low-fat meat emulsions at temperatures over 55 °C. Low-fat meat batters containing wheat flour and apple fibre exhibited the highest rigidity values over the given temperature range. The presence of wheat flour caused variations in the modulus of rigidity at all stages of the thermal gelation process, very similar to those observed in high-fat emulsions.     

Predictors of user perceptions of web recommender systems: How the basis for generating experience and search product recommendations affects user responses

One critical question suggested by Web 2.0 is as follows: When is it better to leverage the knowledge of other users vs. rely on the product characteristic-based metrics for online product recommenders? Three recent and notable changes of recommender systems have been as follows: (1) a shift from characteristic-based recommendation algorithms to social-based recommendation algorithms; (2) an increase in the number of dimensions on which algorithms are based; and (3) availability of products that cannot be examined for quality before purchase. The combination of these elements is affecting users’ perceptions and attitudes regarding recommender systems and the products recommended by them, but the psychological effects of these trends remain unexplored. The current study empirically examines the effects of these elements, using a 2 (recommendation approach: content-based vs. collaborative-based, within)×2 (dimensions used to generate recommendations: 6 vs. 30, between)×2 (product type: experience products (fragrances) vs. search products (rugs), between) Web-based study (N=80). Participants were told that they would use two recommender systems distinguished by recommendation approach (in fact, the recommendations were identical). There were no substantive main effects, but all three variables exhibited two-way interactions, indicating that design strategies must be grounded in a multi-dimensional understanding of these variables. The implications of this research for the psychology and design of recommender systems are presented.     

An efficiently implementable maximum likelihood decoding algorithm for tailbiting codes

Convolutional tailbiting codes are widely used in mobile systems to perform error-correcting strategies of data and control information. Unlike zero tail codes, tailbiting codes do not reset the encoder memory at the end of each data block, improving the code efficiency for short block lengths. The objective of this work is to propose a low-complexity maximum likelihood decoding algorithm for convolutional tailbiting codes based on the Viterbi algorithm. The performance of the proposed solution is compared to that of another maximum likelihood decoding strategy which is based on the A* algorithm. The computational load and the memory requirements of both algorithms are also analysed in order to perform a fair comparison between them. Numerical results considering realistic transmission conditions show the lower memory requirements of the proposed solution, which makes its implementation more suitable for devices with limited resources.     

Residents’ evaluation of advantages and disadvantages of golf community living in Alicante,Spain

The growing numbers of golf communities are attracting a diverse group of homebuyers who experience varying levels of neighborhood satisfaction. A multinomial logistic regression analysis with follow-up ANOVA reveals that homeowners in one region of Spain who believe there are more advantages than disadvantages to living in a golf community are more likely to be older, Spanish, and evaluate the natural environment, sports facilities, and water supply of their community as better. Meanwhile, those who perceive more disadvantages cite the limitations on using the golf course for non-golf activities, high housing costs, automobile dependence, and lack of services and shops. Thus, satisfaction with the golf community varies depending on the residents’ personal characteristics as well as their evaluation of the neighborhood’s characteristics, but is not directly attributable to whether they play golf or whether the course was a decisive factor in choosing the house.     

The role of response repetition in task switching.

When switching between tasks, participants are sometimes required to use different response sets for each task. Thus, task switch and response set switch are confounded. In 5 experiments, the authors examined transitions of response within a linear 4-finger arrangement. A random baseline condition was compared with the cuing of specific response subsets grouped by hand or by finger equivalence, and these subsets were examined in both single task and task-switching designs. Results showed that part of the task switch cost is associated with switching between response sets. Furthermore, the analysis revealed a novel effect: When task switching and repetition trials are mixed, a bias towards switching the response and/or hand is found in task repetition trials. Response repetition is hindered when a task switch is expected, even for those trials when a switch of task does not occur. The results demonstrate executive processes involved in task set configuration closely depend on the motoric processing of the response set. The results are also important for current theories of task set control. (PsycINFO Database Record (c) 2010 APA, all rights reserved)