Identification and correction of besouro's faults: impact on test‐driven development experiments

Context. This thesis is framed in experimental software engineering. More concretely, it addresses the problems arisen when assessing process conformance in test-driven development experiments conducted by UPM's Experimental Software Engineering group. Process conformance was studied using the Eclipse's plug-in tool Besouro. It has been observed that Besouro does not work correctly in some circumstances. It creates doubts about the correction of the existing experimental data which render it useless. Aim. The main objective of this work is the identification and correction of Besouro's faults. A secondary goal is fixing the datasets already obtained in past experiments to the maximum possible extent. This way, existing experimental results could be used with confidence. Method. (1) Testing Besouro using different sequences of events (creation methods, assertions etc..) to identify the underlying faults. (2) Fix the code and (3) fix the datasets using code specially created for this purpose. Results. (1) We confirmed the existence of several fault in Besouro's code that affected to Test-First and Test-Last episode identification. These faults caused the incorrect identification of 20% of episodes. (2) We were able to fix Besouro's code. (3) The correction of existing datasets was possible, subjected to some restrictions (such us the impossibility of tracing code size increase to programming time. Conclusion. The results of past experiments dependent upon Besouro's data could no be trustable. We have the suspicion that more faults remain in Besouro's code, whose identification requires further analysis.

Correction of systematic errors in Wide Area Multilateration

This work presents a method to estimate and correct slow time-dependent position errors due to non perfect ground station synchronization and tropospheric propagation. It uses opportunity traffic emissions, i.e. signals transmitted from the aircrafts within the coverage zone. This method is used to overcome the difficulty of installing reference beacons simultaneously visible by all the base stations in a given Wide Area Multilateration (WAM) system.

Self-learning of fault diagnosis identification

A good and early fault detection and isolation system along with efficient alarm management and fine sensor validation systems are very important in today¿s complex process plants, specially in terms of safety enhancement and costs reduction. This paper presents a methodology for fault characterization. This is a self-learning approach developed in two phases. An initial, learning phase, where the simulation of process units, without and with different faults, will let the system (in an automated way) to detect the key variables that characterize the faults. This will be used in a second (on line) phase, where these key variables will be monitored in order to diagnose possible faults. Using this scheme the faults will be diagnosed and isolated in an early stage where the fault still has not turned into a failure.

Distributed Fault Diagnosis Using Bayesian Reasoning in MAGNETO

Many of the emerging telecom services make use of Outer Edge Networks, in particular Home Area Networks. The configuration and maintenance of such services may not be under full control of the telecom operator which still needs to guarantee the service quality experienced by the consumer. Diagnosing service faults in these scenarios becomes especially difficult since there may be not full visibility between different domains. This paper describes the fault diagnosis solution developed in the MAGNETO project, based on the application of Bayesian Inference to deal with the uncertainty. It also takes advantage of a distributed framework to deploy diagnosis components in the different domains and network elements involved, spanning both the telecom operator and the Outer Edge networks. In addition, MAGNETO features self-learning capabilities to automatically improve diagnosis knowledge over time and a partition mechanism that allows breaking down the overall diagnosis knowledge into smaller subsets. The MAGNETO solution has been prototyped and adapted to a particular outer edge scenario, and has been further validated on a real testbed. Evaluation of the results shows the potential of our approach to deal with fault management of outer edge networks.

Fast Correction of Tiled Display Systems on Planar Surfaces

A method for fast colour and geometric correction of a tiled display system is presented in this paper. Such kind of displays are a common choice for virtual reality applications and simulators, where a high resolution image is required. They are the cheapest and more flexible alternative for large image generation but they require a precise geometric and colour correction. The purpose of the proposed method is to correct the projection system as fast as possible so in case the system needs to be recalibrated it doesn’t interfere with the normal operation of the simulator or virtual reality application. This technique makes use of a single conventional webcam for both geometric and photometric correction. Some previous assumptions are made, like planar projection surface and negligibleintra-projector colour variation and black-offset levels. If these assumptions hold true, geometric and photometric seamlessness can be achievedfor this kind of display systems. The method described in this paper is scalable for an undefined number of projectors and completely automatic.

Tiled Projector Displays Correction for Dark Scenes in Railway Simulators

Tiled projector displays are a common choice for training simulators, where a high resolution output image is required. They are cheap for the resolution that they can reach and can be configured in many different ways. Nevertheless, such kinds of displays require geometric and color correction so that the composite image looks seamless. Display correction is an even bigger challenge when the projected images include dark scenes combined with brighter scenes. This is usually a problem for railway simulators when the train is positioned inside a tunnel and the black offset effect becomes noticeable. In this paper, a method for fast photometric and geometric correction of tiled display systems where dark and bright scenes are combined is presented. The image correction is carried out in two steps. First, geometric alignment and overlapping areas attenuation for brighter scenes is applied. Second, in the event of being inside a tunnel, the brightness of the scene is increased in certain areas using light sources in order to create the impression of darkness but minimizing the effect of the black offset

Study of the evolution of the seismic cycle of stress and strain associated to the El Salvador Fault Zone

• Central America: – Regional studies in Central America (Seismic Hazard). – El Salvador Fault Zone (ESFZ). – Aguacaliente‐Navarro Fault Zone (ANFZ), Central Valley of Costa Rica. – Haiti (seismic hazard) • Spain: – Regional‐Nacional studies of seismic hazards (applications to building codes, eurocode, emergency plans, etc.) – Betic range zone, south of Spain. – Ibero‐Maghrebi region (collision zone)

Fault Tolerance Analysis and Self-Healing Strategy of Autonomous, Evolvable Hardware Systems

This paper presents an analysis of the fault tolerance achieved by an autonomous, fully embedded evolvable hardware system, which uses a combination of partial dynamic reconfiguration and an evolutionary algorithm (EA). It demonstrates that the system may self-recover from both transient and cumulative permanent faults. This self-adaptive system, based on a 2D array of 16 (4×4) Processing Elements (PEs), is tested with an image filtering application. Results show that it may properly recover from faults in up to 3 PEs, that is, more than 18% cumulative permanent faults. Two fault models are used for testing purposes, at PE and CLB levels. Two self-healing strategies are also introduced, depending on whether fault diagnosis is available or not. They are based on scrubbing, fitness evaluation, dynamic partial reconfiguration and in-system evolutionary adaptation. Since most of these adaptability features are already available on the system for its normal operation, resource cost for self-healing is very low (only some code additions in the internal microprocessor core)

A mathematical framework for new fault detection schemes in nonlinear stochastic continuous-time dynamical systems

n this work, a mathematical unifying framework for designing new fault detection schemes in nonlinear stochastic continuous-time dynamical systems is developed. These schemes are based on a stochastic process, called the residual, which reflects the system behavior and whose changes are to be detected. A quickest detection scheme for the residual is proposed, which is based on the computed likelihood ratios for time-varying statistical changes in the Ornstein–Uhlenbeck process. Several expressions are provided, depending on a priori knowledge of the fault, which can be employed in a proposed CUSUM-type approximated scheme. This general setting gathers different existing fault detection schemes within a unifying framework, and allows for the definition of new ones. A comparative simulation example illustrates the behavior of the proposed schemes.

Correction of one unstable embankment in Spain

During the years 1992-1996 a climatic change took place in the Iberian Peninsula, changing from dry years to humid years, giving place to numerous and abundant rainfalls that, in the zone of Andalusia caused enough problems in embankments of the roads.

A multi-agent system with distributed bayesian reasoning for network fault diagnosis

In this paper, an innovative approach to perform distributed Bayesian inference using a multi-agent architecture is presented. The final goal is dealing with uncertainty in network diagnosis, but the solution can be of applied in other fields. The validation testbed has been a P2P streaming video service. An assessment of the work is presented, in order to show its advantages when it is compared with traditional manual processes and other previous systems.

Damage assessment on building structures subjected to the recent near-fault earthquake in Lorca (Spain)

The city of Lorca (Spain) was hit on May 11th 2011 by two consecutive earthquakes with 4.6 and 5.2 Mw respectively, causing casualties and important damage in buildings. Lorca is located in the south-east region of Spain and settled on the trace of the Murcia-Totana-Lorca fault. Although the magnitudes of these ground motions were not severe, the damage observed was considerable over a great amount of buildings. More than 300 of them have been demolished and many others are being retrofitted. This paper reports a field study on the damage caused by these earthquakes. The observed damage is related with the structural typology. Further, prototypes of the damaged buildings are idealized with nonlinear numerical models and their seismic behavior and proneness to damage concentration is further investigated through dynamic response analyses.

Fault detection and isolation on a noisy nonlinear circuit

In this paper fault detection and isolation (FDI) schemes are applied in the context of the surveillance of emerging faults in an electrical circuit. The FDI problem is studied on a noisy nonlinear circuit, where both abrupt and incipient faults in the voltage source are considered. A rigorous analysis of fault detectability precedes the application of the fault detection (FD) scheme; then, the fault isolation (FI) phase is accomplished with two alternative FI approaches, proposed as new extensions of that FD approach. Numerical simulations illustrate the applicability of the mentioned schemes.

Synchronous Buck converter with Output Impedance Correction Circuit

This work is related to the improvement of the output impedance of the Buck converter by means of introducing an additional power path that virtually increases the output capacitance during transients. It is well known that in VRM applications, with wide load steps, voltage overshoots and undershoots may lead to undesired performance of the load. To solve this problem, high-bandwidth high-switching frequency power converters can be applied to reduce the transient time or a big output capacitor can be applied to reduce the output impedance. The first solution can degrade the efficiency by increasing switching losses of the MOSFETS, and the second solution is penalizing the cost and size of the output filter. The Output Impedance Correction Circuit (OICC), as presented here, is used to inject or extract a current n-1 times larger than the output capacitor current, thus virtually increasing n times the value of the output capacitance during the transients. This feature allows the usage of a low frequency Buck converter with smaller capacitor but satisfying the dynamic requirements.

Simulation-based evaluation of susceptibility distortion correction methods in diffusion MRI for connectivity analysis

Connectivity analysis on diffusion MRI data of the whole-brain suffers from distortions caused by the standard echo-planar imaging acquisition strategies. These images show characteristic geometrical deformations and signal destruction that are an important drawback limiting the success of tractography algorithms. Several retrospective correction techniques are readily available. In this work, we use a digital phantom designed for the evaluation of connectivity pipelines. We subject the phantom to a “theoretically correct” and plausible deformation that resembles the artifact under investigation. We correct data back, with three standard methodologies (namely fieldmap-based, reversed encoding-based, and registration- based). Finally, we rank the methods based on their geometrical accuracy, the dropout compensation, and their impact on the resulting connectivity matrices.