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New Models for Automatic Detection of Performance Degradation
Stupinský, Šimon ; Češka, Milan (referee) ; Rogalewicz, Adam (advisor)
Performance testing is a critical factor in the optimisation of programs during its development, but it is still not so well developed in comparison to functional testing. A framework Perun provides full automation of performance management, thereby contributing to the development of this area. We have introduced three non-parametric approaches to performance data modelling: regressogram, moving average and kernel regression, which were integrated within this framework. We try to achieve appropriate approximations of performance data using these techniques, without the assumption of dependence between two variables, which represents the main advantage in comparison to parametric techniques. Further, we have proposed and implemented two methods for automatic detection of performance changes, which works with all kinds of models within Perun . We have demonstrated our solutions on the real project ( Vim ), and on the set of the experimental cases, in which we compared proposed solutions with existing. We have achieved decreased time processing about two-thirds and an almost triple improvement in the fitness of data modelling with new modelling approaches. The proposed detection methods detected performance degradation of three specific functions in comparison of two different versions of Vim, where was present a known performance issue.
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Biomedical data visualization using Matlab
Zvončák, Vojtěch ; Mekyska, Jiří (referee) ; Galáž, Zoltán (advisor)
The thesis deals with the visualization of biomedical data in MATLAB environment. The thesis contains following statistical methods and their descriptions: P-P plot, Q-Q plot, histogram, box plot, kernel denstity estimation, scatter plot and several time series metrics. Some functions are programmed from buil-in functions of MATLAB and others using external functions, which are changed to fit to this thesis’s purpose. First part of the thesis conserns theoretical background, whereas the second part conserns practical programmed realizations of mentioned functions. The program contains a graphical user interface - GUI, which the thesis describes in detail. The purpose of the GUI is to ensure ease of use and also data processing. The output graphs of GUI are shown in chapter 5. The last part deals with the possible extensions of the program.
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Kernel estimates of hazard function
Selingerová, Iveta ; Horová, Ivanka (advisor) ; Prášková, Zuzana (referee)
Kernel estimates of hazard function Abstract This doctoral dissertation is devoted to methods for analysis of censored data in survival analysis. The main attention is focused on the hazard function that reflects the instantaneous probability of the event occurrence within the next time instant. The thesis introduces two approaches for a kernel esti- mation of this function. In practice, the hazard function can be affected by other variables. The most frequently used model suggested by D. R. Cox is presented and moreover two types of kernel estimates to estimate a condi- tional hazard function are proposed. For kernel estimates, there is derived some statistical properties and proposed methods of bandwidths selection. The part of the thesis is extensive simulation study where theoretical results are verified and the proposed methods are compared. The last chapter of the thesis is devoted to an analysis of real data sets obtained from different fields.
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New Models for Automatic Detection of Performance Degradation
Stupinský, Šimon ; Češka, Milan (referee) ; Rogalewicz, Adam (advisor)
Performance testing is a critical factor in the optimisation of programs during its development, but it is still not so well developed in comparison to functional testing. A framework Perun provides full automation of performance management, thereby contributing to the development of this area. We have introduced three non-parametric approaches to performance data modelling: regressogram, moving average and kernel regression, which were integrated within this framework. We try to achieve appropriate approximations of performance data using these techniques, without the assumption of dependence between two variables, which represents the main advantage in comparison to parametric techniques. Further, we have proposed and implemented two methods for automatic detection of performance changes, which works with all kinds of models within Perun . We have demonstrated our solutions on the real project ( Vim ), and on the set of the experimental cases, in which we compared proposed solutions with existing. We have achieved decreased time processing about two-thirds and an almost triple improvement in the fitness of data modelling with new modelling approaches. The proposed detection methods detected performance degradation of three specific functions in comparison of two different versions of Vim, where was present a known performance issue.
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|
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Kernel estimates of hazard function
Selingerová, Iveta ; Horová, Ivanka (advisor) ; Prášková, Zuzana (referee)
Kernel estimates of hazard function Abstract This doctoral dissertation is devoted to methods for analysis of censored data in survival analysis. The main attention is focused on the hazard function that reflects the instantaneous probability of the event occurrence within the next time instant. The thesis introduces two approaches for a kernel esti- mation of this function. In practice, the hazard function can be affected by other variables. The most frequently used model suggested by D. R. Cox is presented and moreover two types of kernel estimates to estimate a condi- tional hazard function are proposed. For kernel estimates, there is derived some statistical properties and proposed methods of bandwidths selection. The part of the thesis is extensive simulation study where theoretical results are verified and the proposed methods are compared. The last chapter of the thesis is devoted to an analysis of real data sets obtained from different fields.
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|
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Biomedical data visualization using Matlab
Zvončák, Vojtěch ; Mekyska, Jiří (referee) ; Galáž, Zoltán (advisor)
The thesis deals with the visualization of biomedical data in MATLAB environment. The thesis contains following statistical methods and their descriptions: P-P plot, Q-Q plot, histogram, box plot, kernel denstity estimation, scatter plot and several time series metrics. Some functions are programmed from buil-in functions of MATLAB and others using external functions, which are changed to fit to this thesis’s purpose. First part of the thesis conserns theoretical background, whereas the second part conserns practical programmed realizations of mentioned functions. The program contains a graphical user interface - GUI, which the thesis describes in detail. The purpose of the GUI is to ensure ease of use and also data processing. The output graphs of GUI are shown in chapter 5. The last part deals with the possible extensions of the program.
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