Asheetoxy: A Taxonomy for Classifying Negative Spreadsheet-related Phenomena

TL;DR

This paper introduces Asheetoxy, a new taxonomy for classifying negative phenomena in spreadsheets that avoids ambiguous terminology and is easy for both researchers and practitioners to apply.

Contribution

The paper presents Asheetoxy, a simple, phenomenon-oriented taxonomy that improves classification consistency and usability over existing error taxonomies in spreadsheet research.

Findings

Participants could classify spreadsheet phenomena consistently using Asheetoxy.

Asheetoxy avoids the ambiguous term 'error' and simplifies classification.

Initial study shows broad applicability beyond spreadsheet experts.

Abstract

Spreadsheets (sometimes also called Excel programs) are powerful tools which play a business-critical role in many organizations. However, due to faulty spreadsheets many bad decisions have been taken in recent years. Since then, a number of researchers have been studying spreadsheet errors. However, one issue that hinders discussion among researchers and professionals is the lack of a commonly accepted taxonomy. Albeit a number of taxonomies for spreadsheet errors have been proposed in previous work, a major issue is that they use the term error that itself is already ambiguous. Furthermore, to apply most existing taxonomies, detailed knowledge about the underlying process and knowledge about the "brain state" of the acting spreadsheet users is required. Due to these limitations, known error-like phenomena in freely available spreadsheet corpora cannot be classified with these taxonomies. We propose Asheetoxy, a simple and phenomenon-oriented taxonomy that avoids the problematic term error altogether. An initial study with 7 participants indicates that even non-spreadsheet researchers similarly classify real-world spreadsheet phenomena using Asheetoxy.