Can observational techniques help novices overcome the software inspection learning curve? An empirical investigation

When learning a new software engineering technique, there is a learning curve that must be overcome. In particular, when studies are conducted in a classroom setting, researchers need a method for quickly accelerating the experience of novice subjects to allow the results to be more applicable in industrial settings. In this paper, we propose and test a method to enable novices to gain process experience to allow them to more quickly overcome the learning curve. The method we evaluate allows an inspector to gain experience with the inspection process by observing an inspection performed by someone else. The results of the study show that the proposed method for gaining experience appears to be useful in some limited cases, that is, for low experienced subjects who were inspecting a requirements document from a domain in which they had low knowledge. Based on the results of this study, we are able to propose some new related hypotheses to be tested in future studies.     

Stability of active disturbance rejection control for uncertain systems: A Lyapunov perspective

In this work, we introduce a simple stability analysis to justify, under some suitable assumptions, the active disturbance rejection control method, used in the feedback regulation of a substantially uncertain plant. A criterion is obtained that allows us to define under what conditions closed‐loop stability can be assured. When the plant is mostly unknown, the criterion allows us to guarantee exponential convergence for the output‐feedback regulation problem, in the presence of a constant external perturbation, and practical stability when the external perturbation and the tracking reference signal are both time‐varying. In the latter case, the confinement error can be made as small as desired. To carry out the corresponding stability analysis, we derive the tracking error equation, and the observation error equation. To decouple these error equations, we use the Sylvester equation. Finally, we applied the direct Lyapunov method to analyze the corresponding convergence of the observation error and of the tracking error. Copyright © 2017 John Wiley & Sons, Ltd.     

Modeling and correction of multipath interference in time of flight cameras

Multipath interference of light is the cause of important errors in Time of Flight (ToF) depth estimation. This paper proposes an algorithm that removes multipath distortion from a single depth map obtained by a ToF camera. Our approach does not require information about the scene, apart from ToF measurements. The method is based on fitting ToF measurements with a radiometric model. Model inputs are depth values free from multipath interference whereas model outputs consist of synthesized ToF measurements. We propose an iterative optimization algorithm that obtains model parameters that best reproduce ToF measurements, recovering the depth of the scene without distortion. We show results with both synthetic and real scenes captured by commercial ToF sensors. In all cases, our algorithm accurately corrects the multipath distortion, obtaining depth maps that are very close to ground truth data.     

Identification and tracking of robots in an intelligent space using static cameras and an XPFCP

This paper tackles the problem of identification and tracking of multiple robots in an intelligent space using an array of cameras placed in fixed positions within the environment. Several types of agent can be found in an intelligent space: controlled agents (mobile robots) and uncontrolled ones (users and obstacles). The information transferred between the controlled agents and the intelligent space is limited to the control commands sent to the robots and the measurements of the odometers received from the robots. The proposed solution allows the localization of mobile agents, even if they are not robots; however, we have focused on the controlled agents. The proposal does not require prior knowledge or invasive landmarks on board the robots. It starts from the segmentation of different agents in motion that allows obtaining the boundaries of all robots and an estimation of all 3D points that define those boundaries. Then, the identification of the robots is obtained by comparing the components of the linear velocity estimated by the motion segmentation algorithm and received from the odometers. In order to track the robots, an eXtended Particle Filter with Classification Process (XPFCP) is employed. Several experimental tests have been carried out, and the results obtained validate the proposal.     

Further analysis of pneumatic ball gauge calibration data; development of quadratic equations

In earlier papers it was shown that an apparent pressure dependence of effective area of pneumatic ball gauges could be ascribed to non-constancy of effective area as conventionally defined. The relationship between P, the pressure measured at the gauge and F, the force due to load of weights on the ball, was generally better represented by an equation of the form P=a+bF derived from linear least squares analysis of calibration data. It is the objective of the present paper to investigate whether the addition of a quadratic term, cF², would improve the agreement of calculated values of P with known calibration values. Calibration data collected for 8-ball gauges were analyzed using analysis of variance (ANOVA) to infer the significance of the quadratic term. For 7 of 8 gauges, a quadratic term significantly improved agreement between calculated and calibration values of P.     

Building knowledge through families of experiments

Experimentation in software engineering is necessary but difficult. One reason is that there are a large number of context variables and, so, creating a cohesive understanding of experimental results requires a mechanism for motivating studies and integrating results. It requires a community of researchers that can replicate studies, vary context variables, and build models that represent the common observations about the discipline. The paper discusses the experience of the authors, based upon a collection of experiments, in terms of a framework for organizing sets of related studies. With such a framework, experiments can be viewed as part of common families of studies, rather than being isolated events. Common families of studies can contribute to important and relevant hypotheses that may not be suggested by individual experiments. A framework also facilitates building knowledge in an incremental manner through the replication of experiments within families of studies. To support the framework, the paper discusses the experiences of the authors in carrying out empirical studies, with specific emphasis on persistent problems encountered in experimental design, threats to validity, criteria for evaluation, and execution of experiments in the domain of software engineering