ExceLint: Automatically Finding Spreadsheet Formula Errors
This addresses the problem of spreadsheet errors for users in high-stakes domains like finance, offering a novel automated solution that is incremental in improving error detection over existing methods.
The authors tackled the problem of finding formula errors in spreadsheets, which are critical in domains like finance, by developing ExceLint, a static analysis tool that uses an information-theoretic approach to identify surprising disruptions in rectangular regions. The result shows that ExceLint is fast, with a median time of 5 seconds per spreadsheet across 70 spreadsheets, and significantly outperforms state-of-the-art analyses.
Spreadsheets are one of the most widely used programming environments, and are widely deployed in domains like finance where errors can have catastrophic consequences. We present a static analysis specifically designed to find spreadsheet formula errors. Our analysis directly leverages the rectangular character of spreadsheets. It uses an information-theoretic approach to identify formulas that are especially surprising disruptions to nearby rectangular regions. We present ExceLint, an implementation of our static analysis for Microsoft Excel. We demonstrate that ExceLint is fast and effective: across a corpus of 70 spreadsheets, ExceLint takes a median of 5 seconds per spreadsheet, and it significantly outperforms the state of the art analysis.