|Title||An empirical study of end-user behaviour in spreadsheet error detection & correction|
|Authors||Brian Bishop & Kevin McDaid|
Very little is known about the process by which end-user developers detect and correct spreadsheet errors. Any research pertaining to the development of spreadsheet testing methodologies or auditing tools would benefit from information on how end-users perform the debugging process in practice.
Thirteen industry-based professionals and thirty-four accounting & finance students took part in a current ongoing experiment designed to record and analyse end-user behaviour in spreadsheet error detection and correction. Professionals significantly outperformed students in correcting certain error types.
Time-based cell activity analysis showed that a strong correlation exists between the percentage of cells inspected and the number of errors corrected. The cell activity data was gathered through a purpose written VBA Excel plug-in that records the time and detail of all cell selection and cell change actions of individuals.
An important research goal was to determine if there was a correlation between the number of cells inspected and error detection/correction performance.
A scatterplot for errors corrected versus coverage shows a moderate-strong linear relationship.
That is, the more cells that are inspected, the more errors are detected.