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Analysis and Testing of Concurrent Programs
Letko, Zdeněk ; Lourenco, Joao (referee) ; Sekanina, Lukáš (referee) ; Vojnar, Tomáš (advisor)
V disertační práci je nejprve uvedena taxonomie chyb v souběžném zpracování dat a přehled technik pro jejich dynamickou detekci. Následně jsou navrženy nové metriky pro měření synchronizace a souběžného chování programů společně s metodologií jejich odvozování. Tyto techniky se zejména uplatní v testování využívajícím techniky prohledávání prostoru a v saturačním testování. Práce dále představuje novou heuristiku vkládání šumu, jejímž cílem je maximalizace proložení instrukcí pozorovaných během testování. Tato heuristika je porovnána s již existujícími heuristikami na několika testech. Výsledky ukazují, že nová heuristika překonává ty existující v určitých případech. Nakonec práce představuje inovativní aplikaci stochastických optimalizačních algoritmů v procesu testování vícevláknových aplikací. Principem metody je hledání vhodných kombinací parametrů testů a metod vkládání šumu. Tato metoda byla prototypově implementována a otestována na množině testovacích příkladů. Výsledky ukazují, že metoda má potenciál vyznamně vylepšit testování vícevláknových programů.
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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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Metaheuristic optimalization for routing problems
Novák, Vít ; Fábry, Jan (advisor) ; Melechovský, Jan (referee)
Routing problems are ones of the most famous members of the group of the classical optimalization combinatorial problems. Travelling salesman problem and problems derived from it have been attracting mathematics and analysts, since they were firstly formulated, and accelerating a development of new methods and approaches that can be used for a wide range of another real-life problems. This thesis aims to demonstrate an usefulness and a flexibility of shown metaheristic methods. Results are compared with outputs of alternative algorithms or known optimal solutions where it is possible. To fulfill this goal the VBA application has been developed. The results of experiments are presented and the application is decribed in a second part of this thesis. A reader should be sufficiently instructed which way he could choose to solve similar types of problems
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Solving the combinatorial optimization problems with the Ant Colony Optimization metaheuristic method
Chu, Andrej ; Jablonský, Josef (advisor) ; Janáček, Jaroslav (referee) ; Linda, Bohdan (referee)
The Ant Colony Optimization belongs into the metaheuristic methods category and it has been developing quite recently. So far it has shown its capabalities to over-perform other metaheuristic methods in quality of the solutions. This work brings analysis of the possible applications of the method on the classical optimization combinatorial problems -- traveling salesman problem, vehicle routing problem, knapsack problem, generalized assignment problem and maximal clique problem. It also deals with the practical experiments with application on several optimization problems and analysis of the time and memory complexity of such algorithms. The last part of the work is dedicated to the possibility of parallelization of the algorithm, which was result of the application of the ACO method on the traveling salesman problem. It brings analysis of the crucial operations and data synchronization issues, as well as practical example and demonstration of the parallelized version of the algorithm.
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Heuristic Methods for General Routing Problems
Muchna, Jan ; Fábry, Jan (advisor) ; Šindelářová, Irena (referee)
The purpose of this work is an analysis of the current state of heuristic methods and their evaluation based on following attributes: accuracy, speed and quality of coding. The work is divided into 3 sections: an introduction to the general routing problem, methods of evaluations and describtion of tangible heuristics and metaheuristics methods. Following algorithms are depicted - from classical heuristics: Clarke and Wright algorithm, Sweep algorithm, Fisher-Jaikumar algorithm, Repeated matching algorithm, Location based heuristics and Petal heuristics - from metaheuristcs: General methods based on Tabu search, Taburoute algorithm, Adaptive memory method. Particular focus of the work is given to Repeated matching algorithm.
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