|Title||Detecting and visualizing inter-worksheet smells in spreadsheets|
|Authors||Felienne Hermans, Martin Pinzger, & Arie van Deursen|
|Publication||Delft University of Technology|
Spreadsheets are often used in business, for simple tasks, as well as for mission critical tasks such as finance or forecasting. Similar to software, some spreadsheets are of better quality than others, for instance with respect to usability, maintainability or reliability. In contrast with software however, spreadsheets are rarely checked, tested or certified.
In this paper, we aim at developing an approach for detecting smells that indicate weak points in a spreadsheet's design. To that end we first study code smells and transform these code smells to their spreadsheet counterparts.
We then present an approach to detect the smells, and communicate located smells to spreadsheet users with data flow diagrams. We analyzed occurrences of these smells in the EUSES corpus. Furthermore we conducted ten case studies in an industrial setting.
The results of the evaluation indicate that smells can indeed reveal weaknesses in a spreadsheet's design, and that data flow diagrams are an appropriate way to show those weaknesses.
|Also see||Detecting code smells in spreadsheet formulas|
For each of the four inter-worksheet smells, we checked how many spreadsheets in the EUSES corpus contain worksheets with metric values above the 70%, 80% and 90% thresholds.
Feature Envy is the most common smell, with 12.4% of the spreadsheets containing worksheets with metric values above the 70% threshold.