research-article

CheckCell: data debugging for spreadsheets

Authors:

Daniel W. Barowy,

Dimitar Gochev,

Emery D. BergerAuthors Info & Claims

OOPSLA '14: Proceedings of the 2014 ACM International Conference on Object Oriented Programming Systems Languages & Applications

Pages 507 - 523

https://doi.org/10.1145/2660193.2660207

Published: 15 October 2014 Publication History

Abstract

Testing and static analysis can help root out bugs in programs, but not in data. This paper introduces data debugging, an approach that combines program analysis and statistical analysis to automatically find potential data errors. Since it is impossible to know a priori whether data are erroneous, data debugging instead locates data that has a disproportionate impact on the computation. Such data is either very important, or wrong. Data debugging is especially useful in the context of data-intensive programming environments that intertwine data with programs in the form of queries or formulas.

We present the first data debugging tool, CheckCell, an add-in for Microsoft Excel. CheckCell identifies cells that have an unusually high impact on the spreadsheet's computations. We show that CheckCell is both analytically and empirically fast and effective. We show that it successfully finds injected typographical errors produced by a generative model trained with data entry from 169,112 Mechanical Turk tasks. CheckCell is more precise and efficient than standard outlier detection techniques. CheckCell also automatically identifies a key flaw in the infamous Reinhart and Rogoff spreadsheet.

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Index Terms

CheckCell: data debugging for spreadsheets
1. Applied computing
  1. Computers in other domains
    1. Personal computers and PC applications
      1. Spreadsheets
2. Software and its engineering
  1. Software creation and management
    1. Software verification and validation
      1. Software defect analysis
        Software testing and debugging

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cover image ACM Conferences

OOPSLA '14: Proceedings of the 2014 ACM International Conference on Object Oriented Programming Systems Languages & Applications

October 2014

946 pages

ISBN:9781450325851

DOI:10.1145/2660193

General Chair:
Andrew Black
Portland State University, USA
,
Program Chair:
Todd Millstein
University of California, Los Angeles, USA

ACM SIGPLAN Notices Volume 49, Issue 10
OOPSLA '14
October 2014
907 pages
ISSN:0362-1340
EISSN:1558-1160
DOI:10.1145/2714064
Editor:
Andy Gill
University of Kansas, Lawrence, KS
Issue’s Table of Contents

Copyright © 2014 ACM.

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Published: 15 October 2014

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https://doi.org/10.1007/s12596-024-02382-z
Poon PLau MYu YTang S(2024)Spreadsheet quality assurance: a literature reviewFrontiers of Computer Science10.1007/s11704-023-2384-618:2Online publication date: 22-Jan-2024
https://doi.org/10.1007/s11704-023-2384-6
Mazzucato DCampion MUrban C(2024)Quantitative Input Usage Static AnalysisNASA Formal Methods10.1007/978-3-031-60698-4_5(79-98)Online publication date: 4-Jun-2024
https://dl.acm.org/doi/10.1007/978-3-031-60698-4_5
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