A Spreadsheet Auditing Tool Evaluated in an Industrial Context

TL;DR

This paper presents an industrial evaluation of a spreadsheet auditing tool that groups similar formulas to detect errors, validated through a field study of 78 large, frequently updated spreadsheets.

Contribution

It introduces a novel formula similarity-based auditing approach and demonstrates its effectiveness in an industrial setting with real-world spreadsheets.

Findings

Audited 78 spreadsheets with over 60,000 cells.

The tool effectively identified irregularities in formula patterns.

Validation confirmed the tool's usefulness in industrial spreadsheet analysis.

Abstract

Amongst the large number of write-and-throw-away spreadsheets developed for one-time use there is a rather neglected proportion of spreadsheets that are huge, periodically used, and submitted to regular update-cycles like any conventionally evolving valuable legacy application software. However, due to the very nature of spreadsheets, their evolution is particularly tricky and therefore error-prone. In our strive to develop tools and methodologies to improve spreadsheet quality, we analysed consolidation spreadsheets of an internationally operating company for the errors they contain. The paper presents the results of the field audit, involving 78 spreadsheets with 60,446 non-empty cells. As a by-product, the study performed was also to validate our analysis tools in an industrial context. The evaluated auditing tool offers the auditor a new view on the formula structure of the spreadsheet by grouping similar formulas into equivalence classes. Our auditing approach defines three similarity criteria between formulae, namely copy, logical and structural equivalence. To improve the visualization of large spreadsheets, equivalences and data dependencies are displayed in separated windows that are interlinked with the spreadsheet. The auditing approach helps to find irregularities in the geometrical pattern of similar formulas.