his.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Towards minimal mutation analysis: Using the approximated dominator set of mutants
University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre. (Distribuerade realtidssystem (DRTS), Distributed Real-Time Systems)
2019 (English)Report (Other academic)
Abstract [en]

In mutation testing, variants (i.e., mutants) of the software under test are created. Themutants are then used to design tests that can detect the difference between the mutantsand the original software under test. Empirical studies have shown that test suites thatare effective in detecting mutants are also effective in detecting real faults. Mutationanalysis is therefore often used to benchmark effectiveness of other testing techniques.The main drawback of mutation testing is that it is computationally expensive becauseof the large number of mutants to analyze. It is well known that many of these mutantsare redundant and recent studies have shown that the redundancy among the mutantscan be up to 99%. However, identifying which mutants that are redundant is challengingsince this depends on the software under test as well as the specific mutations.

This work aims to combine techniques from areas, such as static analysis and machinelearning, in a process for cost-effective mutation analysis. Such techniques are expectedto provide partial solutions to the problem of avoiding creation of the redundant mutants.The outcome of this research is two-fold: (i) an evaluation of techniques that canbe used to minimize the set of non-redundant mutants that needs to be created, and (ii)a process for mutation analysis combining such minimization techniques. A frameworkwill also be developed to evaluate the minimization techniques and the entire process.

Place, publisher, year, edition, pages
2019. , p. 48
Keywords [en]
mutation analysis, dominator mutants, redundant mutants, mutation testing, software testing, mutant minimization
National Category
Computer and Information Sciences
Research subject
Distributed Real-Time Systems
Identifiers
URN: urn:nbn:se:his:diva-16771OAI: oai:DiVA.org:his-16771DiVA, id: diva2:1304679
Note

Research proposal, PhD programme, University of Skövde

Available from: 2019-04-12 Created: 2019-04-12 Last updated: 2019-04-12Bibliographically approved

Open Access in DiVA

fulltext(452 kB)45 downloads
File information
File name FULLTEXT01.pdfFile size 452 kBChecksum SHA-512
2cf3e2a13d673621ac50e91c2c03992ca551da19c83de3ad3dcd47266bfc42ca1f36f7d8b52c2cc42e1e399f7ffb48fe556808ee844d8158fdcd74f2b7180e7e
Type fulltextMimetype application/pdf

Authority records BETA

Márki, András

Search in DiVA

By author/editor
Márki, András
By organisation
School of InformaticsThe Informatics Research Centre
Computer and Information Sciences

Search outside of DiVA

GoogleGoogle Scholar
Total: 45 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

urn-nbn

Altmetric score

urn-nbn
Total: 174 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf