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
Cluster-Based Test Scheduling Strategies Using Semantic Relationships between Test Specifications
RISE, SICS, Västerås, Sweden.ORCID iD: 0000-0002-8724-9049
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0003-0073-1674
University of Innsbruck, Austria, Sweden.
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0003-0611-2655
Show others and affiliations
2018 (English)In: 5th International Workshop on Requirements Engineering and Testing RET'18, 2018, Vol. F137811, p. 1-4Conference paper, Published paper (Refereed)
Abstract [en]

One of the challenging issues in improving the test efficiency is that of achieving a balance between testing goals and testing resources. Test execution scheduling is one way of saving time and budget, where a set of test cases are grouped and tested at the same time. To have an optimal test execution schedule, all related information of a test case (e.g. execution time, functionality to be tested, dependency and similarity with other test cases) need to be analyzed. Test scheduling problem becomes more complicated at high-level testing, such as integration testing and especially in manual testing procedure. Test specifications at high-level are generally written in natural text by humans and usually contain ambiguity and uncertainty. Therefore, analyzing a test specification demands a strong learning algorithm. In this position paper, we propose a natural language processing (NLP) based approach that, given test specifications at the integration level, allows automatic detection of test cases’ semantic dependencies. The proposed approach utilizes the Doc2Vec algorithm and converts each test case into a vector in n-dimensional space. These vectors are then grouped using the HDBSCAN clustering algorithm into semantic clusters. Finally, a set of cluster-based test scheduling strategies are proposed for execution. The proposed approach has been applied in a sub-system from the railway domain by analyzing an ongoing testing project at Bombardier Transportation AB, Sweden.

Place, publisher, year, edition, pages
2018. Vol. F137811, p. 1-4
Keywords [en]
Software testing, Test scheduling, NLP, Dependency, Clustering, Doc2Vec, Optimization, HDBSCAN
National Category
Computer Systems
Identifiers
URN: urn:nbn:se:mdh:diva-38953DOI: 10.1145/3195538.3195540Scopus ID: 2-s2.0-85051238162ISBN: 9781450357494 (print)OAI: oai:DiVA.org:mdh-38953DiVA, id: diva2:1206004
Conference
5th International Workshop on Requirements Engineering and Testing RET'18, 02 Jun 2018, Gothenburg, Sweden
Projects
ITS-EASY Post Graduate School for Embedded Software and SystemsTOCSYC - Testing of Critical System Characteristics (KKS)MegaMaRt2 - Megamodelling at Runtime (ECSEL/Vinnova)TESTOMAT Project - The Next Level of Test AutomationAvailable from: 2018-05-15 Created: 2018-05-15 Last updated: 2018-08-23Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Authority records BETA

Hatvani, LeoAfzal, Wasif

Search in DiVA

By author/editor
Tahvili, SaharHatvani, LeoAfzal, WasifSaadatmand, MehrdadBohlin, Markus
By organisation
Embedded Systems
Computer Systems

Search outside of DiVA

GoogleGoogle Scholar

doi
isbn
urn-nbn

Altmetric score

doi
isbn
urn-nbn
Total: 43 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