A systematic mapping study of software product lines testing

Context

In software development, Testing is an important mechanism both to identify defects and assure that completed products work as specified. This is a common practice in single-system development, and continues to hold in Software Product Lines (SPL). Even though extensive research has been done in the SPL Testing field, it is necessary to assess the current state of research and practice, in order to provide practitioners with evidence that enable fostering its further development.

Objective

This paper focuses on Testing in SPL and has the following goals: investigate state-of-the-art testing practices, synthesize available evidence, and identify gaps between required techniques and existing approaches, available in the literature.

Method

A systematic mapping study was conducted with a set of nine research questions, in which 120 studies, dated from 1993 to 2009, were evaluated.

Results

Although several aspects regarding testing have been covered by single-system development approaches, many cannot be directly applied in the SPL context due to specific issues. In addition, particular aspects regarding SPL are not covered by the existing SPL approaches, and when the aspects are covered, the literature just gives brief overviews. This scenario indicates that additional investigation, empirical and practical, should be performed.

Conclusion

The results can help to understand the needs in SPL Testing, by identifying points that still require additional investigation, since important aspects regarding particular points of software product lines have not been addressed yet.     

Geometric fusion for a hand-held 3D sensor

Abstract. This article presents a geometric fusion algorithm developed for the reconstruction of 3D surface models from hand-held sensor data. Hand-held systems allow full 3D movement of the sensor to capture the shape of complex objects. Techniques previously developed for reconstruction from conventional 2.5D range image data cannot be applied to hand-held sensor data. A geometric fusion algorithm is introduced to integrate the measured 3D points from a hand-held sensor into a single continuous surface. The new geometric fusion algorithm is based on the normal-volume representation of a triangle, which enables incremental transformation of an arbitrary mesh into an implicit volumetric field function. This system is demonstrated for reconstruction of surface models from both hand-held sensor data and conventional 2.5D range images. Received: 30 August 1999 / Accepted: 21 January 2000     

Modelling and optimization of laminated adaptive shells of revolution

In this paper two shell finite element models are presented for the structural analysis of composite laminated piezoelectric shells. One is an axisymmetric conical frustum with two nodal rings and the other is a conic shell panel with eight nodes. Both models are based in a mixed laminated theory that combines a higher order shear deformation theory for the mechanical displacement field with a layerwise representation with linear functions for the electric potential through each piezoelectric layer. In order to obtain the optimal design sensitivities analysis and optimization techniques based in the nonlinear mathematical programming are used. The design objectives can be the minimization of the deformed structure or the maximization of the natural fundamental frequency and the design variables are the electric potential difference applied to the actuators or the ply thicknesses among others.     

Stress recovery in geometrically nonlinear membranes by a Hu-Washizu finite element formulation

A class of mixed finite elements based on the Hu-Washizu functional is introduced as a strategy to reduce the spurious stress phenomena encountered with standard or displacement-based formulations for geometrically exact membranes. Selected examples compare the performance of this class of elements with that of the standard formulation and demonstrate that reduction of spurious stresses is obtained and that the stresses are more accurate than those optimally sampled in the standard formulation.     

Active control of forced vibrations in adaptive structures using a higher order model

This paper deals with a finite element formulation for active control of forced vibrations, including resonance, of thin plate/shell laminated structures with integrated piezoelectric layers, acting as sensors and actuators, based on third-order shear deformation theory. The finite element model is a single layer triangular nonconforming plate/shell element with 24 degrees of freedom for the generalized displacements, and one electrical potential degree of freedom for each piezoelectric element layer, which are surface bonded or embedded in the laminate.

The Newmark method is considered to calculate the dynamic response of the laminated structures, forced to vibrate in the first natural frequency. To achieve a mechanism of active control of the structure dynamic response, a feedback control algorithm is used, coupling the sensor and active piezoelectric layers. The model is applied in the solution of illustrative cases, and the results are presented and discussed.     

Load modeling at electric power distribution substations using dynamic load parameters estimation

This paper is focused on electric power distribution substations load modeling using dynamic load parameters estimation. The load parameters are estimated using two models: the exponential and the ZIP load models. Since the load bus voltage and parameters are known one can determine the active and reactive power injections of this bus and include these pseudo-measurements in the state estimation in order to improve observability and estimation accuracy. The dynamic parameter estimation is developed using the weighted least squares method in a recursive form and the tests are carried out based on actual measurements. It is shown that the estimated parameters (for both load models) at a distribution substation are valid, since the obtained active and reactive power residuals are very close to zero.     

Psychological and Social Predictors of Changes in Fruit and Vegetable Consumption Over 12 Months Following Behavioral and Nutrition Education Counseling.

This study assessed psychological and social factors predicting 12-month changes in fruit and vegetable consumption achieved by 271 men and women from a low-income population randomized to brief behavioral and nutrition education counseling. Greater increases in fruit and vegetable intake were achieved in the behavioral than in the nutrition education condition (1.49 vs. 0.87 portions per day, p=.021). Increases were predicted by baseline social support for dietary change but not by baseline psychological measures. However, short-term (8-week) changes in dietary self-efficacy, encouragement, anticipated regret, perceived benefits, and knowledge of recommended intake predicted 12-month changes in fruit and vegetable consumption independently of gender, age, ethnicity, income, and baseline intake. These factors accounted for 51% of the superiority of behavioral counseling over nutrition education. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Temporal contexts: Effective text classification in evolving document collections

The management of a huge and growing amount of information available nowadays makes Automatic Document Classification (ADC), besides crucial, a very challenging task. Furthermore, the dynamics inherent to classification problems, mainly on the Web, make this task even more challenging. Despite this fact, the actual impact of such temporal evolution on ADC is still poorly understood in the literature. In this context, this work concerns to evaluate, characterize and exploit the temporal evolution to improve ADC techniques. As first contribution we highlight the proposal of a pragmatical methodology for evaluating the temporal evolution in ADC domains. Through this methodology, we can identify measurable factors associated to ADC models degradation over time. Going a step further, based on such analyzes, we propose effective and efficient strategies to make current techniques more robust to natural shifts over time. We present a strategy, named temporal context selection, for selecting portions of the training set that minimize those factors. Our second contribution consists of proposing a general algorithm, called Chronos, for determining such contexts. By instantiating Chronos, we are able to reduce uncertainty and improve the overall classification accuracy. Empirical evaluations of heuristic instantiations of the algorithm, named WindowsChronos and FilterChronos, on two real document collections demonstrate the usefulness of our proposal. Comparing them against state-of-the-art ADC algorithms shows that selecting temporal contexts allows improvements on the classification accuracy up to 10%. Finally, we highlight the applicability and the generality of our proposal in practice, pointing out this study as a promising research direction.