Error Estimation in Large Spreadsheets using Bayesian Statistics

TL;DR

This paper explores using Bayesian statistical methods to estimate error levels in large spreadsheets, aiding decision-making on testing needs during cell-by-cell review based on expert input and partial data.

Contribution

It introduces a novel application of Bayesian statistics for error estimation in spreadsheets, integrating expert knowledge and partial testing data.

Findings

Bayesian methods provide reliable error estimates.

Estimation can guide testing decisions effectively.

Early research shows promising results.

Abstract

Spreadsheets are ubiquitous in business with the financial sector particularly heavily reliant on the technology. It is known that the level of spreadsheet error can be high and that it is often necessary to review spreadsheets based on a structured methodology which includes a cell by cell examination of the spreadsheet. This paper outlines the early research that has been carried out into the use of Bayesian Statistical methods to estimate the level of error in large spreadsheets during cell be cell examination based on expert knowledge and partial spreadsheet test data. The estimate can aid in the decision as to the quality of the spreadsheet and the necessity to conduct further testing or not.