Asheetoxy: A Taxonomy for Classifying Negative Spreadsheet-related Phenomena
This work addresses the lack of a commonly accepted taxonomy for spreadsheet errors, which hinders discussion among researchers and professionals, though it appears incremental as it builds on existing taxonomies.
The authors tackled the problem of inconsistent classification of negative spreadsheet phenomena by proposing Asheetoxy, a simple and phenomenon-oriented taxonomy that avoids the ambiguous term 'error', with an initial study showing 7 participants could similarly classify real-world spreadsheet phenomena using it.
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.