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Fuzzer Based on Genetic Programming
Závada, Tomáš ; Gerlich, Tomáš (referee) ; Ilgner, Petr (advisor)
The thesis is focused on testing, discusses its various approaches and more specifically focuses on the automated testing technique called fuzzing. It discusses its process, advantages, disadvantages and then also some of its possible improvements. Furthermore, the work is focused specifically on improving the process of fuzzing techniques using genetic algorithms. Genetic algorithms help create more appropriate test inputs, saving time during testing process while achieving appropriate results. A server using the DLMS/COSEM standard was chosen as the testing target. The thesis also introduces the DLMS protocol, which provides communication between clients and servers, and other essentials falling under the COSEM specification. Then the assembly of a test network, containing a server and a client, which use the mentioned standard for communication, is described. The thesis also elaborates a solution proposal for how the connection of the testing tool to the network could look like. Finally, the implementation of a fuzzer using the process of genetic algorithms to generate test data is also included.
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Optimisation of Flow Rates in Lubrication Systems with Progressive Distributors by means of Genetic Algorithms
Vepřek, Jiří ; Pavlok, Bohuslav (referee) ; Bauer, František (referee) ; Habán, Vladimír (referee) ; Nevrlý, Josef (advisor)
This doctoral thesis presents the results of the development of two software programs for the design of progressive distributors and progressive lubrication systems. One of these programs implements a genetic algorithm and the other, which is used to design progressive lubrication systems, implements a parallel genetic algorithm of the island model. The program for the design of progressive distributors was implemented in Java using the NetBeans development environment and the other program was created in Matlab. The thesis further focuses on analytical and computational solutions of the flow of compressible greases seen as viscoplastic fluids. Equations for the numerical solution of the non-steady flow of compressible viscoplastic Bingham fluids were derived and solved by the Lax-Wendroff method in Matlab. As several constants had to be set in the equations, experiments were conducted with the ecological grease Plantogel 2S in the laboratory of the Kaplan Department of Hydraulic Machines, mainly to determine the sound velocity in this grease. The sound velocity was calculated based on the experimental results by applying Fourier transformation and the transition matrix method. In addition to this, the rheological measurements of greases were used. As seen from the results, the ecological greases are actually thixotropic viscoplastic fluids with a significant elastic element. Since a Newton fluid was assumed when calculating the sound velocity, the possibilities of using the transition matrix method for viscoplastic fluids were then considered. No analytical solution of the flow of viscoplastic fluids in a frequency spectrum has been published so far. Because it emerged that greases had a significant elastic stress factor, the problem of the non-steady flow of elastic-viscoplastic fluids was solved numerically between two infinite parallel plates by applying the finite difference method (FDM). The computation was done in Matlab. This doctoral thesis makes a contribution to solving problems related to the design of progressive distributors and progressive lubrication systems used to distribute compressible greases. Considering the complex approach to this field and the achieved results, the thesis also represents a significant contribution to design work.
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Technical Analysis
Kosek, Lukáš ; Doubravský, Karel (referee) ; Novotná, Veronika (advisor)
This thesis deals with problems of the technical analyses and its usage during creation of the automated trading systems. Theoretical section explains the basic principles of functioning of the monetary market (Forex) and includes technical indicators. Portfolio of strategies, as output of this work, was applied onto monetary pairs of Euro/American dollar and British pound/American dollar. Computer program Adaptrade Builder was used for proposed commercial strategies with help of the genetic algorithms and subsequently tested on the MetaTrader 4 commercial platform.
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Test Optimization by Search-Based Algorithms
Starigazda, Michal ; Holík, Lukáš (referee) ; Letko, Zdeněk (advisor)
Testing of multi-threaded programs is a demanding work due to the many possible thread interleavings one should examine. The noise injection technique helps to increase the number of tested thread interleavings by noise injection to suitable program locations. This work optimizes meta-heuristics search techniques in the testing of concurrent programs by utilizing deterministic heuristic in the application of genetic algorithms in a space of legal program locations suitable for the noise injection. In this work, several novel deterministic noise injection heuristics without dependency on the random number generator are proposed in contrary to the most of currently used heuristic. The elimination of the randomness should make the search process more informed and provide better, more optimal, solutions thanks to increased stability in the results provided by novel heuristics. Finally, a benchmark of programs, used for the evaluation of novel noise injection heuristics is presented.
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Evolutionary Optimization of Control Algorithms
Weisser, Roman ; Šeda, Miloš (referee) ; Zelinka,, Ivan (referee) ; Ošmera, Pavel (advisor)
The dissertation thesis deals with Evolution optimization of control algorithms. The first part of the thesis describes the principles and partial methods of evolution optimization methods especially those used in two-level transplant evolution method. Later the grammatical evolution method is described, which modified algorithm became impulse for creation of transplant evolution method. The transplant evolution method and its two-level modification are new evolutionary algorithms proposed in this work, which were used for optimization of structure and parameters of general controllers control algorithms. The transplant evolution algorithm and its extended two-level modification are described in detail in next chapters. The proper settings of evolutionary algorithms are important for minimization the time of optimization and for finds results approaching the global optimum. For proper setting the parameters of differential evolution was created meta-evolution algorithm that is described in chapter named meta-evolution. The basic concepts of control, chosen methods of system identification and controller parameters settings are described in next part. This part describes algorithms of digital controllers and some specific methods uses in digital control. The demonstrations of control algorithm optimizations of various types of controllers are showed in experimental part. The optimized algorithms of general controllers are compared with various types of PSD controllers which were set by various algebraic methods or differential evolution for various models of systems. In the conclusion of this work is stated a recommendation for further development of evolutionary optimization of controllers are focusing on parallel and distributed computing.
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Application of Genetic Algorithms and Data Mining in Noise-based Testing of Concurrent Software
Šimková, Hana ; Kofroň, Jan (referee) ; Lourenco, Joao (referee) ; Vojnar, Tomáš (advisor)
Tato práce navrhuje zlepšení výkonu testování programů použitím technik dolování z dat a genetických algoritmů při testování paralelních programů. Paralelní programování se v posledních letech stává velmi populárním i přesto, že toto programování je mnohem náročnějsí než jednodušší sekvenční a proto jeho zvýšené používání vede k podstatně vyššímu počtu chyb. Tyto chyby se vyskytují v důsledku chyb v synchronizaci jednotlivých procesů programu. Nalezení takových chyb tradičním způsobem je složité a navíc opakované spouštění těchto testů ve stejném prostředí typicky vede pouze k prohledávání stejných prokládání. V práci se využívá metody vstřikování šumu, která vystresuje program tak, že se mohou objevit některá nová chování. Pro účinnost této metody je nutné zvolit vhodné heuristiky a též i hodnoty jejich parametrů, což není snadné. V práci se využívá metod dolování z dat, genetických algoritmů a jejich kombinace pro nalezení těchto heuristik a hodnot parametrů. V práci je vedle výsledků výzkumu uveden stručný přehled dalších Technik testování paralelních programů.
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The Shortest Graph's Pahts Finding
Jágr, Petr ; Ohlídal, Miloš (referee) ; Jaroš, Jiří (advisor)
The aim of this thesis is finding, comparing and implementation of algorithms for finding the shortest paths between each of pairs of nodes in a graph. For this task I use modifications of existing algorithms to achive the lowest time consumption of the computation. Modifications are established on Dijkstra's and Floyd-Warshall's algorithm. We also familiarize with Bellman-Ford algorithm.
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Evolutionary Algorithms in Convolutional Neural Network Design
Badáň, Filip ; Vašíček, Zdeněk (referee) ; Sekanina, Lukáš (advisor)
This work focuses on automatization of neural network design via the so-called neuroevolution, which employs evolutionary algorithms to construct artificial neural networks or optimise their parameters. The goal of the project is to design and implement an evolutionary algorithm which can be used in the process of designing and optimizing topologies of convolutional neural networks. The effectiveness of the proposed framework was experimentally evaluated on tasks of image classification on datasets MNIST and CIFAR10 and compared with relevant solutions. The results showed that neuroevolution has a potential to successfully find accurate and effective convolutional neural network architectures.
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