mdh.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • 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
On Measuring Combinatorial Coverage of Manually Created Test Cases for Industrial Software
Mälardalen University.
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0003-2416-4205
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0003-0611-2655
2019 (English)In: International Conference on Software Testing, Verification and Validation Workshops ICSTW19, 2019, p. 264-267Conference paper, Published paper (Refereed)
Abstract [en]

Combinatorial coverage has been proposed as a way to measure the quality of test cases by using the input interaction characteristics. This paper describes the results of empirically measuring combinatorial coverage of manually created test cases by experienced industrial engineers. We found that manual test cases achieve on average 78% 2-way combinatorial coverage, 57% 3-way coverage, 40% 4-way coverage, 20% 5-way combinatorial coverage and 13% for 6-way combinatorial coverage. These manual test cases can be augmented to achieve 100% combinatorial coverage for 2-way and 3-way interactions by adding eight and 66 missing tests on average, respectively. For 4-way interactions, full combinatorial coverage can achieved by adding 658 missing tests. For 5-way and 6-way interactions, full combinatorial coverage can be achieved by adding 5163 and 6170 missing tests on average, respectively. The results of this paper suggest that manual tests created by industrial engineers do no achieve high combinatorial coverage and can be improved by using combinatorial testing at the expense of the number of test cases to be executed.

Place, publisher, year, edition, pages
2019. p. 264-267
National Category
Engineering and Technology Computer Systems
Identifiers
URN: urn:nbn:se:mdh:diva-43914DOI: 10.1109/ICSTW.2019.00062ISI: 000477742600038OAI: oai:DiVA.org:mdh-43914DiVA, id: diva2:1326109
Conference
12th IEEE International Conference on Software Testing, Verification and Validation (ICST), 22 Apr 2019, Xian, China
Projects
MegaMaRt2 - Megamodelling at Runtime (ECSEL/Vinnova)XIVT - eXcellence in Variant TestingAvailable from: 2019-06-17 Created: 2019-06-17 Last updated: 2019-08-15Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full text

Authority records BETA

Enoiu, Eduard PaulAfzal, Wasif

Search in DiVA

By author/editor
Fifo, MiraldiEnoiu, Eduard PaulAfzal, Wasif
By organisation
Mälardalen UniversityEmbedded Systems
Engineering and TechnologyComputer Systems

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 3 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • 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