The Examination of Shall Be Impossible Situations for Verification During Execution
American Journal of Computer Science and Technology
Volume 1, Issue 2, June 2018, Pages: 44-54
Received: Feb. 18, 2018;
Accepted: Mar. 5, 2018;
Published: Mar. 23, 2018
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Rimantas Seinauskas, Software Department, Informatic Faculty, Kaunas University of Technology, Kaunas, Lithuania
Runtime verification is looking for violations of the properties of the system functioning. Finding and describing the system properties that indicate behavioural disorders is a complex and labour-intensive process that needs to be automated. This article describes how system properties can be determined automatically during the correct functioning. Inspection of the combinations of fulfilled properties makes it possible to detect more system problems. Three methods of handling property combinations are offered. The methods are based on the examination of the input sequences and output results. In order to increase the volume of the properties of the system under consideration, only the possible pairs of properties are analysed. Pairs are formed from the output properties, as well as from the input conditions and output properties, and the maximum possible number of property pairs is evaluated. The available property pairs are captured during the operation. Impossible combinations of properties that never occur during the execution highlight situations that are not possible during proper functioning. Capture of impossible property pairs during verification indicates system problems. During the experiment, five types of disorders and three detection methods were considered. Experimental results show that there is no single best method for detecting disorders. Therefore, it is appropriate at the same time to use several methods to detect disorders. The experiment shows how much of the disorders can detect the proposed approach.
The Examination of Shall Be Impossible Situations for Verification During Execution, American Journal of Computer Science and Technology.
Vol. 1, No. 2,
2018, pp. 44-54.
Copyright © 2018 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/
) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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