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Open access

Marek Żukowicz

Abstract

The aim of the article is to highlight the advantages that can be obtained through the use of evolutionary strategy in software testing, specifically in the process of test data generation. The first chapter introduces the reader to the topic of the article. Presents information of the problem of software quality, test data fitness and quality criteria. The second chapter provides an overview of the publication in which is described the test data generation problem by using evolutionary strategies. In this chapter there are presented, different approaches to address the optimization problem of test data selection. The third chapter sets out the advantages which in the opinion of the author result from the application of evolutionary strategy in the process of test data generation. In this section have been drawn conclusions from the article, from books listed in the bibliography. The author of the article presents advantages of evolutionary strategy too as a person, which tests a software in practise. The last chapter in addition to summaries and conclusions, proposes the author to suggest in which issues related to testing could be used evolutionary strategies.

Open access

Marek Żukowicz and Michał Markiewicz

Abstract

The aim of the article is to present a mathematical definition of the object model, that is known in computer science as TreeList and to show application of this model for design evolutionary algorithm, that purpose is to generate structures based on this object. The first chapter introduces the reader to the problem of presenting data using the TreeList object. The second chapter describes the problem of testing data structures based on TreeList. The third one shows a mathematical model of the object TreeList and the parameters, used in determining the utility of structures created through this model and in evolutionary strategy, that generates these structures for testing purposes. The last chapter provides a brief summary and plans for future research related to the algorithm presented in the article.