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Prioritizing Tests with Spotify’s Test & Build Data using History-based, Modification-based & Machine Learning Approaches
Linköping University, Department of Computer and Information Science, Software and Systems.
2017 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

This thesis intends to determine the extent to which machine learning can be used to solve the regression test prioritization (RTP) problem. RTP is used to order tests with respect to probability of failure. This will optimize for a fast failure, which is desirable if a test suite takes a long time to run or uses a significant amount of computational resources. A common machine learning task is to predict probabilities; this makes RTP an interesting application of machine learning. A supervised learning method is investigated to train a model to predict probabilities of failure, given a test case and a code change. The features investigated are chosen based on previous research of history- based and modification-based RTP. The main motivation for looking at these research areas is that they resemble the data provided by Spotify. The result of the report shows that it is possible to improve how tests run with RTP using machine learning. Nevertheless, a much simpler history- based approach is the best performing approach. It is looking at the history of test results, the more failures recorded for the test case over time, the higher priority it gets. Less is sometimes more. 

Place, publisher, year, edition, pages
2017. , p. 43
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:liu:diva-138705ISRN: LIU-IDA/LITH-EX-A--2017/021--SEOAI: oai:DiVA.org:liu-138705DiVA, id: diva2:1113227
External cooperation
Spotify AB
Subject / course
Computer Engineering
Presentation
2017-06-07, TP40, Bredgatan 33, 60221 Norrköping, 15:15 (English)
Supervisors
Examiners
Available from: 2017-06-22 Created: 2017-06-21 Last updated: 2018-01-13Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
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  • 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