In this chapter an introduction to model checking and model learning was given. Furthermore, it was shown how to combine both techniques to an approach in which properties of a SUT are verified directly. First of all ...
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In this chapter an introduction to model checking and model learning was given. Furthermore, it was shown how to combine both techniques to an approach in which properties of a SUT are verified directly. First of all we have presented Kripke transition systems which build a simple basis for temporal logics used in model checking. The essential difference between linear time logics and branching time logics was made plain on the basis of an example. Subsequently we presented linear time logic (LTL) and computational tree logic (CTL) which are widely used for model checking purposes. Since the combination of model checking and model learning for testing purposes is only meaningful with linear time logics we presented a basic model checking algorithm for linear time logic. In the second part of the chapter we first gave an introduction to the general ideas of model learning algorithms. Continuing in the same subject, we presented a number of learning algorithms;the observation pack algorithm, Angluin's algorithm, the reduced observation table algorithm and, the discrimination tree algorithm. Subsequently we discussed the algorithms' query complexity and presented some domain specific optimizations to reduce the number of queries. We rounded the model learning part off with some experimental results. The final part in this chapter presented the adaptive model checking algorithm, which combines model checking and model learning into one approach. The approach try to make use of information in an existing model of the SUT in order to save effort in the learning procedure. If no model exist or the existing model is irrelevant compared to the current SUT, the approach is still applicable. Although model checking and model learning are both established research areas, a lot of work remains to be done when considering testing. The combination of model checking and testing techniques should be clarified. Models to be used for testing might ask for different characteristics of
Peculiarities of constructing ensemble bagging classifiers for identifying the state of a computer system under conditions of noisy data are studied. Decision trees and multilayer perceptron were used as basic classif...
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The paper presents a new technique for the botnets' detection in the corporate area networks. It is based on the usage of the algorithms of the artificial immune systems. Proposed approach is able to distinguish b...
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Let G be a connected graph of n vertices. The problem of finding a depth-first spanning tree of G is to find a connected subgraph of G with the n vertices and n - 1 edges by depth-first-search. In this paper, we propo...
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This paper presents a one machine multiple-product problem with bounded production rate to minimize the total linear cost of inventory under imprecise space constraint. The demand is dependent on time and known. Also ...
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A new technique for the DDoS botnet detection based on the botnets network features analysis is proposed. It uses the semi-supervised fuzzy c-means clustering. The proposed approach includes the learning and the detec...
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This paper presents a novel method on coloring the grayscale images. For this purpose, a combination of artificial neural networks and some image processing algorithms was developed to transfer colors from a user-sele...
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Theoretical results for identifying unnecessary inferences are discussed in the context of the use of a completion-procedure-based approach toward automated reasoning. The notion of a general superposition is introduc...
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Theoretical results for identifying unnecessary inferences are discussed in the context of the use of a completion-procedure-based approach toward automated reasoning. The notion of a general superposition is introduced and it is proved that in a completion procedure, once a general superposition is considered, all its instances are unnecessary inferences and, thus, do not have to be considered. It is also shown that this result can be combined with another criterion, called the prime superposition criterion, proposed by Kapur, Musser, and Narendran, thus implying that prime and general superpositions are sufficient. These results should be applicable to other approaches toward automated reasoning, too. These criteria can be effectively implemented, and their implementation has resulted in automatically proving instances of Jacobson's theorem (also known as the ring commutativity problems) usingRRL (Rewrite Rule Laboratory), a theorem prover based on rewriting techniques and completion.
This paper introduces a ranking function procedure on a bi-level programming for Stackelberg game involving intuitionistic fuzzy *** fuzzy num-ber is considered in many real-life situations,so it makes perfect sense t...
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This paper introduces a ranking function procedure on a bi-level programming for Stackelberg game involving intuitionistic fuzzy *** fuzzy num-ber is considered in many real-life situations,so it makes perfect sense to address decision-making problem by using some specified intuitionistic fuzzy *** this paper,intuitionistic fuzziness is characterized by a normal generalized triangular intuitionistic fuzzy number.A defuzzification method is introduced based on the pro-portional probability density function associated with the corresponding membership function,as well as the complement of non-membership *** the proposed ranking technique,a methodology is presented for solving bi-level programming for Stackelberg *** application example is provided to demonstrate the applica-bility of the proposed methodology,and the achieved results are compared with the existing methods.
The purpose of this paper is automating the analysis of tourist demand by developing a web-service for surveying tourists (both real and potential) and for presenting the survey results in the form of determining the ...
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