• DocumentCode
    635296
  • Title

    1st International workshop on data analysis patterns in software engineering (DAPSE 2013)

  • Author

    Bird, Christian ; Menzies, Tim ; Zimmermann, Thomas

  • Author_Institution
    Microsoft Research, USA
  • fYear
    2013
  • fDate
    18-26 May 2013
  • Firstpage
    1517
  • Lastpage
    1518
  • Abstract
    Data scientists in software engineering seek insight in data collected from software projects to improve software development. The demand for data scientists with domain knowledge in software development is growing rapidly and there is already a shortage of such data scientists. Data science is a skilled art with a steep learning curve. To shorten that learning curve, this workshop will collect best practices in form of data analysis patterns, that is, analyses of data that leads to meaningful conclusions and can be reused for comparable data. In the workshop we compiled a catalog of such patterns that will help experienced data scientists to better communicate about data analysis. The workshop was targeted at experienced data scientists and researchers and anyone interested in how to analyze data correctly and efficiently in a community accepted way.
  • Keywords
    Conferences; Data analysis; Data mining; Sociology; Software; Software engineering; Statistics; big data; business intelligence; data mining; data science; machine learning; predictive analytics; smart data; software analytics; software engineering; software intelligence;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Software Engineering (ICSE), 2013 35th International Conference on
  • Conference_Location
    San Francisco, CA, USA
  • Print_ISBN
    978-1-4673-3073-2
  • Type

    conf

  • DOI
    10.1109/ICSE.2013.6606765
  • Filename
    6606765