• DocumentCode
    695465
  • Title

    University-industry collaboration and open source software (OSS) dataset in mining software repositories (MSR) research

  • Author

    Tripathi, Ambika ; Dabral, Savita ; Sureka, Ashish

  • Author_Institution
    Indraprastha Inst. of Inf. Technol., Delhi, India
  • fYear
    2015
  • fDate
    2-2 March 2015
  • Firstpage
    39
  • Lastpage
    40
  • Abstract
    Mining Software Repositories (MSR) is an applied and practise-oriented field aimed at solving real problems encountered by practitioners and bringing value to Industry. We believe that empirical studies on both Open Source Software (OSS) and Closed or Proprietary Source (CSS/PSS) is required in MSR research to increase generalizability or transferability of findings and reduce external (or threats) validity concerns. Furthermore, we believe that a collaboration between University and Industry is must or important in achieving the stated goals and agenda of MSR research (such as deployment and technology transfer). We analyse past five years of research papers published in MSR series of conferences (2010-2014) and count the number of studies using solely OSS data or solely CSS data or both OSS and CSS data. We also count the number of papers published by authors solely from Universities, solely from Industry and from both University and Industry. We present our findings which indicate lack of University-Industry collaboration (measured using co-authorship in scientific publications) and paucity of empirical studies on CSS/PSS data. Our analysis reveals that out of 187 studies over a period of 5 years, 90:9% studies are conducted solely on OSS dataset. We present our findings which indicate that only 14:43% of the studies involve a University-Industry collaboration.
  • Keywords
    data analysis; educational institutions; organisational aspects; public domain software; research initiatives; software engineering; CSS data; MSR research; OSS data; closed or proprietary source; coauthorship; mining software repositories; open source software dataset; scientific publications; university-industry collaboration; Bibliometrics; Cascading style sheets; Collaboration; Data mining; Industries; Software; Software engineering; Empirical Software Engineering; Generalizabilityand External Validity Concerns; Mining Software Repositories(MSR); Open Source Software (OSS) Dataset; University-IndustryCollaboration;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Software Analytics (SWAN), 2015 IEEE 1st International Workshop on
  • Conference_Location
    Montreal, QC
  • Type

    conf

  • DOI
    10.1109/SWAN.2015.7070489
  • Filename
    7070489