A spreadsheet cell-meaning model for testing - Daniel Kulesz at Sems 2014
14
SEMS 2014 Daniel Kulesz Institute of Software Technology University of Stuttgart [email protected] A Spreadsheet Cell-Meaning Model for Testing 2 nd July 2014
-
Upload
semsworkshop -
Category
Technology
-
view
657 -
download
1
Transcript of A spreadsheet cell-meaning model for testing - Daniel Kulesz at Sems 2014
SEMS 2014
Daniel Kulesz
Institute of Software TechnologyUniversity of Stuttgart
A Spreadsheet Cell-Meaning Modelfor Testing
2nd July 2014
A Spreadsheet Cell-Meaning Model for Testing SEMS 2014
© Daniel Kulesz
2 / 14
Agenda
Introduction
Issues with the “naive” cell-meaning model
Requirements for a better model
Our prototype
Future work
A Spreadsheet Cell-Meaning Model for Testing SEMS 2014
© Daniel Kulesz
3 / 14
Introduction
Spreadsheet failures can cause problems – sometimes with severe impact.
Detecting anomalies (errors, defects, faults, failures...) in spreadsheets early can prevent failures in the field.
Several anomaly detection techniques exist. The most prominent for detecting failures is testing.
Testing: Input cells are populated with data. Afterwards, “output” cells are checked for deviations between expected and actual results.
System testing: end-to-endTerminology borrowedfrom IEEE Std. 1044-2009
A Spreadsheet Cell-Meaning Model for Testing SEMS 2014
© Daniel Kulesz
4 / 14
Cell-Meaning Models
Cell-Meaning Models (my notion) describe or prescribe what specific spreadsheet cells mean to the user.
Cell meanings can be automatically detected using the internal re/calculation model of spreadsheet environments:
Input cells
Intermediate calculation cells
Result cells
Plausibility cells (just one approach)
Existing testing approaches use this “Naive Cell-Meaning Model”.
My claim: The Naive Model is too limited for testing.
A Spreadsheet Cell-Meaning Model for Testing SEMS 2014
© Daniel Kulesz
5 / 14
ExampleSpreadsheet for managing course grades
Collaborative setting:
Filled by course instructor
Passed to secretary
Used for statistical purposes by study program manager
A Spreadsheet Cell-Meaning Model for Testing SEMS 2014
© Daniel Kulesz
6 / 14
Example: Detected cell-meanings
Input cells
Intermediatecalculation cells
Result cells
A Spreadsheet Cell-Meaning Model for Testing SEMS 2014
© Daniel Kulesz
7 / 14
Issue 1Total points could be output values (secretary), but are auto-detected as intermediate cells.
A Spreadsheet Cell-Meaning Model for Testing SEMS 2014
© Daniel Kulesz
8 / 14
Issue 2 Plausibility cells are not output cells.
A Spreadsheet Cell-Meaning Model for Testing SEMS 2014
© Daniel Kulesz
9 / 14
Issue 3Just the failure rate is a meaningful output cell for the study program manager.
A Spreadsheet Cell-Meaning Model for Testing SEMS 2014
© Daniel Kulesz
10 / 14
Issue 4Static data cells are not input cells for any of the users.
A Spreadsheet Cell-Meaning Model for Testing SEMS 2014
© Daniel Kulesz
11 / 14
Issue 5 Student names are input cells,too (course instructor).
A Spreadsheet Cell-Meaning Model for Testing SEMS 2014
© Daniel Kulesz
12 / 14
Requirements for a better model
From a theoretic perspective:
User-specifiable
Support for views
Input cells must distinguish between “dumb data” and “decision variables”
Output cells must distinguish between “real results” and “plausibility statements”
From a practical perspective:
Understandability
Acceptance
A Spreadsheet Cell-Meaning Model for Testing SEMS 2014
© Daniel Kulesz
13 / 14
Our prototype
Partly implemented* in our tool“Spreadsheet inspection framework”
See it in action tomorrow in the tooldemo track at EuSpRIG!
* no view support yet and just threecell-meaning types so far.
A Spreadsheet Cell-Meaning Model for Testing SEMS 2014
© Daniel Kulesz
14 / 14
Future work
Finish implementation
Validate understandability
Validate acceptance
Are the benefits of the model worth the effort of manual intervention in the cell-meaning detection process?
Questions?
