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ASE 2018

Noise and heterogeneity in historical build data: an empirical study of Travis CI

Keheliya Gallaba, Christian Macho, Martin Pinzger, Shane McIntosh

PDFDOI 10.1145/3238147.3238171dblp

Abstract

Automated builds, which may pass or fail, provide feedback to a development team about changes to the codebase. A passing build indicates that the change compiles cleanly and tests (continue to) pass. A failing (a.k.a., broken) build indicates that there are issues that require attention. Without a closer analysis of the nature of build outcome data, practitioners and researchers are likely to make two critical assumptions: (1) build results are not noisy; however, passing builds may contain failing or skipped jobs that are actively or passively ignored; and (2) builds are equal; however, builds vary in terms of the number of jobs and configurations.

BibTeX
@inproceedings{Gallaba-al:ASE18,
  author    = {Keheliya Gallaba and
               Christian Macho and
               Martin Pinzger and
               Shane McIntosh},
  title     = {Noise and heterogeneity in historical build data: an empirical study of Travis {CI}},
  booktitle = {ASE},
  pages     = {87--97},
  publisher = {{ACM}},
  year      = {2018},
}

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