CheckCell

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.

ExceLint: automatically finding spreadsheet formula errors

“…ExceLint extracts reference vectors by first gathering data dependencies for every formula in the given spreadsheet. It obtains dependence information by parsing a sheet's formulas and building the program's dataflow graph [Barowy et al 2014;Cooper and Torczon 2005]. ExceLint can analyze all Excel functions.…”

“…The cutoff threshold is a user-defined parameter that represents the proportion of the worksheet that a user is willing to inspect. The default value, 5%, is based on the observed frequency of spreadsheet errors in the wild [Barowy et al 2014;Panko 2015]. Users may adjust this threshold to inspect more or fewer cells, depending on their preference.…”

“…The EUSES corpus collects spreadsheets used as databases, and for financial, grading, homework, inventory, and modeling purposes. EUSES is frequently used by researchers building spreadsheet tools [Alawini et al 2015;Barowy et al 2014Barowy et al , 2015Cheung et al 2016;Grigoreanu et al 2010;Hermans and Dig 2014;Hermans et al 2012aHermans et al , 2010Hermans et al , 2013Hofer et al 2013;Joharizadeh 2015;Le and Gulwani 2014;Muşlu et al 2015;Singh et al 2017]. All of the categories present in EUSES are represented in the CUSTODES suite.…”