Debugging is one of the most time-consuming activities in software development. Several fault localization techniques have been proposed in the last years, aiming to reduce development costs. A promising approach, called Spectrum-based Fault localization (SFL), consists of techniques that provide a list of suspicious program elements (e.g., statements, basic blocks, methods) more likely to be faulty. Developers should inspect a suspiciousness list to search for faults. However, these fault localization techniques are not yet used in practice. These techniques are based on assumptions about the developer\'s behavior when inspecting such lists that may not hold in practice. A developer is supposed to inspect an SFL list from the most to the least suspicious program elements (e.g., statements) until reaching the faulty one. This assumption leads to some implications: the techniques are assessed only by the position of a bug in a list; a bug is deemed as found when the faulty element is reached. SFL techniques should pinpoint the faulty program elements among the first picks to be useful in practice. Most techniques use ranking metrics to assign suspiciousness values to program elements executed by the tests. These ranking metrics have presented similar modest results, which indicates the need for different strategies to improve the effectiveness of SFL. Moreover, most techniques use only control-flow spectra due to the high execution costs associated with other spectra, such as data-flow. Also, little research has investigated the use of SFL techniques by practitioners. Understanding how developers use SFL may help to clarify the theoretical assumptions about their behavior, which in turn can collaborate with the proposal of techniques more feasible for practical use. Therefore, user studies are a valuable tool for the development of the area. The goal of this thesis research was to propose strategies to improve spectrum-based fault localization, focusing on its practical use. This thesis presents the following contributions. First, we investigate strategies to provide contextual information for SFL. These strategies helped to reduce the amount of code to be inspected until reaching the faults. Second, we carried out a user study to understand how developers use SFL in practice. The results show that developers can benefit from SFL to locate bugs. Third, we explore the use of data-flow spectrum for SFL. Data-flow spectrum singles out faults significantly better than control-flow spectrum, improving the fault localization effectiveness. / Depuração é uma das atividades mais custosas durante o desenvolvimento de programas. Diversas técnicas de localização de defeitos têm sido propostas nos últimos anos com o objetivo de reduzir custos de desenvolvimento. Uma abordagem promissora, chamada Localização de Defeitos baseada em Espectro (LDE), é formada por técnicas que fornecem listas contendo elementos de código (comandos, blocos básicos, métodos) mais suspeitos de conter defeitos. Desenvolvedores deveriam inspecionar uma lista de suspeição para procurar por defeitos. No entanto, essas técnicas de localização de defeitos ainda não são usadas na prática. Essas técnicas baseiam-se em suposições sobre o comportamento de desenvolvedores durante a inspeção de tais listas que podem não ocorrer na prática. Um desenvolvedor supostamente inspeciona uma lista de LDE a partir do elemento mais suspeito para o menos suspeito até atingir o elemento defeituoso. Essa suposição leva a algumas implicações: as técnicas são avaliadas somente pela posição dos defeitos nas listas; um defeito é considerado como encontrado quando o elemento defeituoso é atingido. Técnicas de LDE deveriam posicionar os elementos de código defeituosos entre as primeiras posições para serem úteis na prática. A maioria das técnicas usa métricas de ranqueamento para atribuir valores de suspeição aos elementos executados pelos testes. Essas métricas de ranqueamento têm apresentado resultados semelhantes, o que indica a necessidade de estratégias diferentes para melhorar a eficácia de LDE. Além disso, a maioria das técnicas usa somente espectros de fluxo de controle devido ao alto custo de execução associado a outros espectros, tais como fluxo de dados. Também, poucas pesquisas têm investigado o uso de técnicas de LDE por programadores. Entender como desenvolvedores usam LDE pode ajudar a esclarecer as suposições teóricas sobre seu comportamento, o que por sua vez pode para colaborar para a proposição de técnicas mais viáveis para uso prático. Portanto, estudos com usuários são importantes para o desenvolvimento da área. O objetivo desta pesquisa de doutorado foi propor estratégias para melhorar a localização de defeitos baseada em espectro focando em seu uso prático. Esta tese apresenta as seguintes contribuições originais. Primeiro, nós investigamos estratégias para fornecer informação de contexto para LDE. Essas estratégias ajudaram a reduzir quantidade de código a ser inspecionado até atingir os defeitos. Segundo, nós realizamos um estudo com usuários para entender como desenvolvedores usam LDE na prática. Os resultados mostram que desenvolvedores podem beneficiar-se de LDE para localizar defeitos. Terceiro, nós exploramos o uso de espectros de fluxo de dados para LDE. Mostramos que o espectro de fluxo de dados seleciona defeitos significamente melhor que espectro de fluxo de controle, aumentando a eficácia de localização de defeitos.

The most widespread system of an earthing neutral point of a supply transformer in a MV network is an earthing through an arc-suppression coil. In this case of a resonant-earthed power system a fault current is compensated by the suppression coil and only residual current flows through a fault point. A value of the residual current is much smaller then a value of an original capacitive current of the network and is not dependent on the fault location. According to that reasons it is really complicated to fast and accurately determine the fault point location. Since nowadays used methods for the ground fault location inside wide distribution networks have a lot of disadvantages, the thesis is focused on a proposal of a new method for the ground fault location especially inside of a compensated network. The main reasons for a consecutive installation of power quality meters into distribution transformer substations are a power quality monitoring and a global evolution of an electrical network onto the “SmartGrids”. In case that all results from the meters are properly synchronized and centralized, new possibilities of control or of an evaluation of a network are enabled. This doctoral thesis proposes the possibility for the ground fault detection with an aid of synchronized records recorded on the low-voltage side of the distribution transformers 22/0.4 kV into the network equipped with automatics for short-time increasing of an active part of a faulty current. The described method uses a voltage drop evoked by connecting of the auxiliary resistor for location of the faulty section. The proposed method is tested with help of numerical model which presents a part of the distribution network Series of simulation are executed and correct function and force function of the method is reviewed. Finally the thesis describes real experiment and also a confrontation between simulation and real measuring, and also possibilities of method usage are commented.

This Master's thesis is focused on creating of an algorithm which calculates changes of negative-sequence voltages and currents from their instantaneous values. That allows to conduct localization of asymmetrical faults in MV network in line with the Vdip method, which is based on monitoring the changes of negative-sequence components at distribution substations and at a sub-transmission station. The algorithm is being developed in Matlab environment with continuous implementation of partial procedures which are being assessed and compared with each other. A study of phasor estimating methods is carried out with pointing out related problems which are mainly caused by Ripple control and deviation of system frequency from its nominal value. Optimization precautions are designed to mitigate these problems. For elimination of the Ripple control effects a method based on averaging is presented. The deviation of system frequency is dealt with by resampling the original data recordings. The analysis processes are tested by both simulation signals and real measured data. The optimized algorithm enables precise calculation of negative-sequence components changes which is the main contribution of this thesis. The constructed algorithm is used in verification of the Vdip method on physical model of MV network. For these purposes a simple distribution network is created within which ground faults on different places and with different resistances are realised. The results of localization are not convincing which is mainly caused by specific features of laboratory power line models which are constructed with heterogenous parameters.

Les réseaux de télécommunications deviennent de plus en plus complexes, notamment de par la multiplicité des technologies mises en œuvre, leur couverture géographique grandissante, la croissance du trafic en quantité et en variété, mais aussi de par l’évolution des services fournis par les opérateurs. Tout ceci contribue à rendre la gestion de ces réseaux de plus en plus lourde, complexe, génératrice d’erreurs et donc coûteuse pour les opérateurs. On place derrière le terme « réseaux autonome » l’ensemble des solutions visant à rendre la gestion de ce réseau plus autonome. L’objectif de cette thèse est de contribuer à la réalisation de certaines fonctions autonomiques dans les réseaux de télécommunications. Nous proposons une stratégie pour automatiser la gestion des pannes tout en couvrant les différents segments du réseau et les services de bout en bout déployés au-dessus. Il s’agit d’une approche basée modèle qui adresse les deux difficultés du diagnostic basé modèle à savoir : a) la façon d'obtenir un tel modèle, adapté à un réseau donné à un moment donné, en particulier si l'on souhaite capturer plusieurs couches réseau et segments et b) comment raisonner sur un modèle potentiellement énorme, si l'on veut gérer un réseau national par exemple. Pour répondre à la première difficulté, nous proposons un nouveau concept : l’auto-modélisation qui consiste d’abord à construire les différentes familles de modèles génériques, puis à identifier à la volée les instances de ces modèles qui sont déployées dans le réseau géré. La seconde difficulté est adressée grâce à un moteur d’auto-diagnostic actif, basé sur le formalisme des réseaux Bayésiens et qui consiste à raisonner sur un fragment du modèle du réseau qui est augmenté progressivement en utilisant la capacité d’auto-modélisation: des observations sont collectées et des tests réalisés jusqu’à ce que les fautes soient localisées avec une certitude suffisante. Cette approche de diagnostic actif a été expérimentée pour réaliser une gestion multi-couches et multi-segments des alarmes dans un réseau IMS. / While modern networks and services are continuously growing in scale, complexity and heterogeneity, the management of such systems is reaching the limits of human capabilities. Technically and economically, more automation of the classical management tasks is needed. This has triggered a significant research effort, gathered under the terms self-management and autonomic networking. The aim of this thesis is to contribute to the realization of some self-management properties in telecommunication networks. We propose an approach to automatize the management of faults, covering the different segments of a network, and the end-to-end services deployed over them. This is a model-based approach addressing the two weaknesses of model-based diagnosis namely: a) how to derive such a model, suited to a given network at a given time, in particular if one wishes to capture several network layers and segments and b) how to reason a potentially huge model, if one wishes to manage a nation-wide network for example. To address the first point, we propose a new concept called self-modeling that formulates off-line generic patterns of the model, and identifies on-line the instances of these patterns that are deployed in the managed network. The second point is addressed by an active self-diagnosis engine, based on a Bayesian network formalism, that consists in reasoning on a progressively growing fragment of the network model, relying on the self-modeling ability: more observations are collected and new tests are performed until the faults are localized with sufficient confidence. This active diagnosis approach has been experimented to perform cross-layer and cross-segment alarm management on an IMS network.

Liberalized electricity markets, increased awareness of clean energy resources and theirdecreasing costs have resulted in large numbers of distributed power generators beinginstalled on distribution network. Installation of distributed generation has altered thepassive nature of distribution grid. A concept of Active Distribution Network is proposedwhich will enable present day infrastructure to host renewable energy resources reliably.Fault management that includes fault localization, isolation and service restoration ispart of active management of distribution networks.This thesis aims to introduce a distributed protection methodology for fault localizationand isolation. The objective is to enhance reliability of the network. Faults are identifiedbased on root mean square values of current measurements and by comparing thesevalues with preset thresholds. The method based on multi-agent concept can be usedto locate the faulty section of a distribution network and for selection of faulty phases.The nodal Bus Agent controls breakers that are associated with it. Based on indicationof fault, adjacent bus Agents communicate with each other to identify location of fault.A trip signal is then issued to corresponding Breakers in adjacent Bus Agents, isolatingthe faulty section of line. A case study was carried out to verify suitability of the proposedmethod. A meshed network model and multi-agent based protection scheme wassimulated in Simulink SimPowerSystems. Considering nature of Distribution Network,separate breakers for each phase are considered. The distribution network protectionsystem identified fault introduced in the network correctly along with interrupting thefault current.Keywords

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Submitted by Franciele Moreira (francielemoreyra@gmail.com) on 2018-10-30T13:30:59Z No. of bitstreams: 2 Dissertação - Diogo Machado de Freitas - 2018.pdf: 1477764 bytes, checksum: 73759c5ece96bf48ffd4d698f14026b9 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Approved for entry into archive by Luciana Ferreira (lucgeral@gmail.com) on 2018-10-30T13:41:38Z (GMT) No. of bitstreams: 2 Dissertação - Diogo Machado de Freitas - 2018.pdf: 1477764 bytes, checksum: 73759c5ece96bf48ffd4d698f14026b9 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Made available in DSpace on 2018-10-30T13:41:38Z (GMT). No. of bitstreams: 2 Dissertação - Diogo Machado de Freitas - 2018.pdf: 1477764 bytes, checksum: 73759c5ece96bf48ffd4d698f14026b9 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Previous issue date: 2018-09-24 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES / Fault Localization is one stage of the software life cycle, which demands important resources such as time and effort spent on a project. There are several initiatives towards the automation of the fault localization process and the reduction of the associated resources. Many techniques are based on heuristics that use information obtained (spectrum) from the execution of test cases, in order to measure the suspiciousness of each program element to be defective. Spectrum data generally refers to code coverage and test results (positive or negative). The present work presents two approaches based on the Genetic Programming algorithm for the problem of Fault Localization: a method to compose a new heuristic from a set of existing ones; and a method for constructing heuristics based on data from program mutation analysis. The innovative aspects of both methods refer to the joint investigation of: (i) specialization of heuristics for certain programs; (ii) application of an evolutionary approach to the generation of heuristics with non-linear equations; (iii) creation of heuristics based on the combination of traditional heuristics; (iv) use of coverage and mutation spectra extracted from the test activity; (v) analyzing and comparing the efficacy of methods that use coverage and mutation spectra for fault localization; and (vi) quality analysis of the mutation spectra as a data source for fault localization. The results have pointed to the competitiveness of both approaches in their contexts. / Localização de Defeitos é uma etapa do ciclo de vida de software, que demanda recursos importantes tais como o tempo e o esforço gastos em um projeto. Existem diversas iniciativas na direção da automação do processo de localização de defeitos e da redução dos recursos associados. Muitas técnicas são baseadas heurísticas que utilizam informação obtida (espectro) a partir da execução de casos de teste, visando a medir a suspeita de cada elemento de programa para ser defeituoso. Os dados de espectro referem-se, em geral, à cobertura de código e aos resultados dos teste (positivo ou negativo). O presente trabalho apresenta duas abordagens baseadas no algoritmo Programação Genética para o problema de Localização de Defeitos: um método para compor automaticamente novas heurísticas a partir de um conjunto de heurísticas existentes; e um método para a construção de heurísticas baseadas em dados oriundos da análise de mutação de programas. Os aspectos inovadores de ambos os métodos referem-se à investigação conjunta de: (i) especialização de heurísticas para determinados programas; (ii) aplicação de abordagem evolutiva para a geração de heurísticas com equações não lineares; (iii) criação de heurísticas a partir da combinação de heurísticas tradicionais; (iv) uso de espectro de cobertura e de mutação extraídos da atividade de teste; (v) análise e comparação da eficácia de métodos que usam os espectros de cobertura e de mutação para a localização de defeitos; e (vi) análise da qualidade dos espectros de mutação como fonte de dados para a localização de defeitos. Os resultados apontaram competitividade de ambas as abordagens em seus contextos.

Les réseaux de télécommunication doivent être fiables et robustes pour garantir la haute disponibilité des services. Les opérateurs cherchent actuellement à automatiser autant que possible les opérations complexes de gestion des réseaux, telles que le diagnostic de pannes.Dans cette thèse nous nous sommes intéressés au diagnostic automatique de pannes dans les réseaux d'accès optiques de l'opérateur Orange. L'outil de diagnostic utilisé jusqu'à présent, nommé DELC, est un système expert à base de règles de décision. Ce système est performant mais difficile à maintenir en raison, en particulier, du très grand volume d'informations à analyser. Il est également impossible de disposer d'une règle pour chaque configuration possible de panne, de sorte que certaines pannes ne sont actuellement pas diagnostiquées.Dans cette thèse nous avons proposé une nouvelle approche. Dans notre approche, le diagnostic des causes racines des anomalies et alarmes observées s'appuie sur une modélisation probabiliste, de type réseau bayésien, des relations de dépendance entre les différentes alarmes, compteurs, pannes intermédiaires et causes racines au niveau des différents équipements de réseau. Ce modèle probabiliste a été conçu de manière modulaire, de façon à pouvoir évoluer en cas de modification de l'architecture physique du réseau.Le diagnostic des causes racines des anomalies est effectué par inférence, dans le réseau bayésien, de l'état des noeuds non observés au vu des observations (compteurs, alarmes intermédiaires, etc...) récoltées sur le réseau de l'opérateur. La structure du réseau bayésien, ainsi que l'ordre de grandeur des paramètres probabilistes de ce modèle, ont été déterminés en intégrant dans le modèle les connaissances des experts spécialistes du diagnostic sur ce segment de réseau. L'analyse de milliers de cas de diagnostic de pannes a ensuite permis de calibrer finement les paramètres probabilistes du modèle grâce à un algorithme EM (Expectation Maximization).Les performances de l'outil développé, nommé PANDA, ont été évaluées sur deux mois de diagnostic de panne dans le réseau GPON-FTTH d'Orange en juillet-août 2015. Dans la plupart des cas, le nouveau système, PANDA, et le système en production, DELC, font un diagnostic identique. Cependant un certain nombre de cas sont non diagnostiqués par DELC mais ils sont correctement diagnostiqués par PANDA. Les cas pour lesquels les deux systèmes émettent des diagnostics différents ont été évalués manuellement, ce qui a permis de démontrer dans chacun de ces cas la pertinence des décisions prises par PANDA. / Telecommunication networks must be reliable and robust to ensure high availability of services. Operators are currently searching to automate as much as possible, complex network management operations such as fault diagnosis.In this thesis we are focused on self-diagnosis of failures in the optical access networks of the operator Orange. The diagnostic tool used up to now, called DELC, is an expert system based on decision rules. This system is efficient but difficult to maintain due in particular to the very large volume of information to analyze. It is also impossible to have a rule for each possible fault configuration, so that some faults are currently not diagnosed.We proposed in this thesis a new approach. In our approach, the diagnosis of the root causes of malfunctions and alarms is based on a Bayesian network probabilistic model of dependency relationships between the different alarms, counters, intermediate faults and root causes at the level of the various network component. This probabilistic model has been designed in a modular way, so as to be able to evolve in case of modification of the physical architecture of the network. Self-diagnosis of the root causes of malfunctions and alarms is made by inference in the Bayesian network model of the state of the nodes not observed in view of observations (counters, alarms, etc.) collected on the operator's network. The structure of the Bayesian network, as well as the order of magnitude of the probabilistic parameters of this model, were determined by integrating in the model the expert knowledge of the diagnostic experts on this segment of the network. The analysis of thousands of cases of fault diagnosis allowed to fine-tune the probabilistic parameters of the model thanks to an Expectation Maximization algorithm. The performance of the developed probabilistic tool, named PANDA, was evaluated over two months of fault diagnosis in Orange's GPON-FTTH network in July-August 2015. In most cases, the new system, PANDA, and the system in production, DELC, make an identical diagnosis. However, a number of cases are not diagnosed by DELC but are correctly diagnosed by PANDA. The cases for which self-diagnosis results of the two systems are different were evaluated manually, which made it possible to demonstrate in each of these cases the relevance of the decisions taken by PANDA.

This master’s thesis is about earth fault locator testing on the model of unsymmetrical lines. The introductory part of thesis describes the function of the selected locator, mainly for the used calculation algorithm of fault location, options setting of fault locator and connection of the locator to the network. Master’s thesis in its practical part deals, with the setting fault locator for a particular test system on the model of the MV line and implementation of selected testing on the model unsymmetrical lines. The first part of the testing is focusing on verify the accuracy locator on an unsymmetrical line. The second test is then designed for obtaining the most accurate information on the distance of the fault, which fault locator can give. The final part is focused on verification algorithm for more accurate calculation of the fault location.

This master's thesis offers a brief introduction to evolutionary computation. It describes and compares the genetic programming and grammar based genetic programming and their potential use in automatic software repair. It studies possible applications of grammar based genetic programming on automatic software repair. Grammar based genetic programming is then used in design and implementation of a new method for automatic software repair. Experimental evaluation of the implemented automatic repair was performed on set of test programs.