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Raising the Quality of Software Development by Data Mining Defect

Raising the Quality of Software Development by Data Mining Defect

Anna Gromova
Head of Data Analysis Department, Exactpro

SECR 2019
14-15 November 2019, Saint Petersburg

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November 14, 2019
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  1. None
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  4. How quickly are bugs fixed? Which software components are the

    most problematic? How are bugs described?
  5. How quickly are bugs fixed? Which software components are the

    most problematic? How are bugs described? Release schedule problem Software quality / technical stability problem Dev./ QA communi cation problem
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  8. Calculated probabilities: • the probability of a software defect belonging

    to a specific area of testing; • the probability of a software defect being rejected; • priority levels; • the probability of a software defect being fixed, including time to resolve.
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  14. Resolution Priority Was reopened? Time to resolve (TTR): min /

    max/ mean 0 / 4321 / 141 Count of attachments: min / max/ mean 0 / 31 / 1 Count of comments: min / max/ mean 0 / 126 / 4
  15. Types of bugs: • “inexpensive-to-resolve”, TTR, count of comments, count

    of attachment <mean, Major, “Done” • “expensive-to-resolve”, TTR, count of comments, count of attachment >=mean • “underestimated” TTR>=mean , Major / Critical / Blocker , “Done”, was reopened • “Invalid”, TTR, count of comments, count of attachment <mean, “Reject” / “Won’t Fix” / “Duplicate” • “longest-to-resolve”, TTR>=mean , Minor, “Out of date” / “Migrated to another IS”
  16. Statistical evaluation Text evaluation How defects are described Particulars of

    the project’s subject domain Characteris tics of the defect fixing Generation of testing metrics Prediction of testing metrics Generation of recommendations
  17. Exactpro’s Nostradamus tool is available on GitHub at https://github.com/Exactpro/nostradamus

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