@INPROCEEDINGS{Zolfagharinia17-MSR-CPANBuilds,
   AUTHOR       = {Mahdis Zolfagharinia and Bram Adams and 
      Yann-Ga�l Gu�h�neuc},
   BOOKTITLE    = {Proceedings of the 14<sup>th</sup> International Conference on Mining Software Repositories (MSR)},
   TITLE        = {Do Not Trust Build Results at Face Value: An Empirical 
      Study of 30 Million CPAN Builds},
   YEAR         = {2017},
   OPTADDRESS   = {},
   OPTCROSSREF  = {},
   EDITOR       = {Lin Tan and Abram Hindle},
   MONTH        = {May},
   NOTE         = {10 pages.},
   OPTNUMBER    = {},
   OPTORGANIZATION = {},
   PAGES        = {312--322},
   PUBLISHER    = {ACM Press},
   OPTSERIES    = {},
   OPTVOLUME    = {},
   KEYWORDS     = {Topic: <b>Program comprehension</b>, Venue: <c>MSR</c>},
   URL          = {http://www.ptidej.net/publications/documents/MSR17b.doc.pdf},
   PDF          = {http://www.ptidej.net/publications/documents/MSR17b.ppt.pdf},
   ABSTRACT     = {Continuous Integration (CI) is a cornerstone of modern 
      quality assurance, providing on-demand builds (compilation and tests) 
      of code changes or software releases. Despite the myriad of CI tools 
      and frameworks, the basic activity of interpreting build results is 
      not straightforward, due to not only the number of builds being 
      performed but also, and especially, due to the phenomenon of build 
      inflation, according to which one code change can be built on dozens 
      of different operating systems, run-time environments and hardware 
      architectures. As existing work mostly ignored this inflation, this 
      paper performs a large-scale empirical study of the impact of OS and 
      run-time environment on build failures on 30 million builds of the 
      CPAN ecosystem's CI environment. We observe the evolution of build 
      failures over time, and investigate the impact of OSes and 
      environments on build failures. We show that distributions may fail 
      differently on different OSes and environments and, thus, that the 
      results of CI require careful filtering and selection to identify 
      reliable failure data.}
}

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