@inproceedings{Muslu15issta,
  author = {K{\i}van{\c{c}} Mu{\c{s}}lu and Yuriy Brun and Alexandra Meliou},
  title =
  {\href{http://people.cs.umass.edu/brun/pubs/pubs/Muslu15issta.pdf}{Preventing Data Errors with Continuous Testing}},
  booktitle = {Proceedings of the ACM SIGSOFT International Symposium on
  Software Testing and Analysis (ISSTA)},
  venue = {ISSTA},
  month = jul,
  year = {2015},
  date = {12--17},
  pages = {373--384},
  address = {Baltimore, MD, USA},
  doi = {10.1145/2771783.2771792},
  accept = {$\frac{33}{119} \approx 28\%$},

  abstract = {Today, software systems that use data are ubiquitous, and ensuring the data's
  quality is an increasingly important challenge as data errors result in
  annual multi-billion dollar losses. While software debugging and testing have
  received heavy research attention, less effort has been devoted to data
  debugging: identifying system errors caused by well-formed but incorrect
  data. We present continuous data testing (CDT), a low-overhead, delay-free
  technique that quickly identifies likely data errors. CDT continuously
  executes domain-specific test queries; when a test fails, CDT unobtrusively
  warns the user or administrator. We implement CDT in the ConTest prototype
  for the PostgreSQL database management system. A user study with 96 humans
  shows that ConTest is extremely effective at guarding against data entry
  errors: With ConTest, users corrected 98.4% of their errors, as opposed to
  40.2% without, even when we injected 40% false positives into ConTest's
  output. Further, when using ConTest, users corrected data entry errors 3.2
  times faster than when using state-of-the-art methods.},
}