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AuthorOtt, Christophdc.contributor.author
Date of accession2016-03-14T15:20:08Zdc.date.accessioned
Available in OPARU since2016-03-14T15:20:08Zdc.date.available
Year of creation2009dc.date.created
AbstractSoftware testing, i.e. the systematic execution of the software with the aim of detecting failures, is an essential part of software quality assurance. There are two main problems in software testing. One of them concerns the choice of adequate test data. The other one is the problem of test evaluation. In order to save time and money it is important to automate both the process of test data generation and test evaluation. Random Testing, i.e. the purely random generation of test data within a predetermined input domain, is one strategy of automatically generating test input data. Random Testing data generation is very fast and rather easy to implement. Moreover, its results are unbiased and allow for statistical prediction. Adaptive Random Testing (ART) has been introduced in order to enhance the effectiveness of Random Testing without using any additional information about the software under test. Since there is empirical evidence that failure-causing inputs appear clustered within the input domain, the aim of ART is to achieve an even spread of test cases inside this domain. Many ART methods have been proposed, so far. This work tries to answer the question how ART can be applied effectively. Therefore, previous methods are analyzed and, since they turn out to be inadequate in many situations, new ART methods are proposed.dc.description.abstract
Languagededc.language.iso
PublisherUniversität Ulmdc.publisher
LicenseStandard (Fassung vom 01.10.2008)dc.rights
Link to license texthttps://oparu.uni-ulm.de/xmlui/license_v2dc.rights.uri
KeywordAdaptive random testingdc.subject
KeywordFailure patterndc.subject
KeywordRandom testingdc.subject
KeywordTest case selectiondc.subject
KeywordTesting effectivenessdc.subject
Dewey Decimal GroupDDC 004 / Data processing & computer sciencedc.subject.ddc
LCSHComputer software; Testingdc.subject.lcsh
TitleZum effektiven Einsatz des Adaptiven Zufallstestsdc.title
Resource typeDissertationdc.type
DOIhttp://dx.doi.org/10.18725/OPARU-1088dc.identifier.doi
PPN601724267dc.identifier.ppn
URNhttp://nbn-resolving.de/urn:nbn:de:bsz:289-vts-68419dc.identifier.urn
GNDSoftwareentwicklungdc.subject.gnd
FacultyFakultät für Mathematik und Wirtschaftswissenschaftenuulm.affiliationGeneral
Date of activation2009-06-04T13:57:11Zuulm.freischaltungVTS
Peer reviewneinuulm.peerReview
Shelfmark print versionZ: J-H 9.810; N: J-H 9.862uulm.shelfmark
DCMI TypeTextuulm.typeDCMI
VTS ID6841uulm.vtsID
CategoryPublikationenuulm.category
Bibliographyuulmuulm.bibliographie


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