On the Effectiveness of Automatically Inferred Invariants in Detecting Regression Faults in Spreadsheets

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

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Abstract

Automatically inferred invariants have been found to be successful in detecting regression faults in traditional software, but their application has not been explored in the context of spreadsheets. In this paper, we investigate the effectiveness of automatically inferred invariants in detecting regression faults in spreadsheets. We conduct an exploratory empirical study on eight spreadsheets taken from VEnron and EUSES corpora. We apply automatic invariant inference to them, create tests based on the inferred invariants, and finally seed the sheets with faults. Results indicate that the effectiveness of the inferred invariants, in terms of accuracy of fault detection, largely varies from spreadsheet to spreadsheet. The effectiveness is found to be affected by the formulas and data contained in the spreadsheets, and also by the type of faults to be detected.
Original languageEnglish
Title of host publicationCompanion of the 18th IEEE International Conference on Software Quality, Reliability, and Security
Place of PublicationPiscataway, NJ
PublisherIEEE
Pages199-206
Number of pages8
ISBN (Electronic)978-1-5386-7839-8
ISBN (Print)978-1-5386-7840-4
DOIs
Publication statusPublished - Jul 2018

Keywords

  • Spreadsheets
  • Invariant Analysis
  • Regression Faults
  • Fault Detection
  • Software Quality
  • End-user Development

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  • Research Output

    • 2 Conference contribution

    Spreadsheet testing in practice

    Roy, S., Hermans, F. & Van Deursen, A., 21 Mar 2017, Proceedings - 24th International Conference on Software Analysis, Evolution and Reengineering, SANER 2017. Pinzger, M., Bavota, G. & Marcus, A. (eds.). Piscataway, NJ: IEEE, p. 338-348 11 p. 7884634

    Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

    Open Access
    File
  • 8 Citations (Scopus)
    282 Downloads (Pure)

    Evaluating Automatic Spreadsheet Metadata Extraction on a Large Set of Responses from MOOC Participants

    Roy, S., Hermans, F., Aivaloglou, E., Winter, J. & van Deursen, A., 2016, 2016 IEEE 23rd International Conference on Software Analysis, Evolution, and Reengineering (SANER). Jiu, A. (ed.). Los Alamitos, CA: IEEE Society, Vol. 2. p. 135-145 11 p.

    Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

    File
  • 72 Downloads (Pure)

    Cite this

    Roy, S., van Deursen, A., & Hermans, F. (2018). On the Effectiveness of Automatically Inferred Invariants in Detecting Regression Faults in Spreadsheets. In Companion of the 18th IEEE International Conference on Software Quality, Reliability, and Security (pp. 199-206). IEEE. https://doi.org/10.1109/QRS-C.2018.00046