Reducing error in spreadsheets: example driven modelling versus traditional programming

Thorne, Simon, Ball, David and Lawson, Zoe Frances 2012. Reducing error in spreadsheets: example driven modelling versus traditional programming. International Journal of Human-Computer Interaction 10.1080/10447318.2012.677744

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Abstract

In this paper we present experimental data supporting an alternative approach to developing decision support spreadsheets using a Programming by Demonstration (PbD) paradigm. This technique is coined “Example Driven Modelling” and uses example data (attribute classifications) in combination with inductive machine learning to create decision support models as an alternative to spreadsheet programming. In this experiment we examine whether participants can define attribute classifications (“example-giving”) satisfactorily and describe benefits and limitations this method offers through statistical analysis of the experimental results. We then consider the wider implications of this research in traditional programming.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Computer Science & Informatics Mathematics
Subjects:	Q Science > QA Mathematics Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software
Additional Information:	Advance online publication
Publisher:	Taylor and Francis
ISSN:	1044-7318
Last Modified:	10 Oct 2017 14:31
URI:	https://orca.cardiff.ac.uk/id/eprint/33639

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