@conference {abreu2014smelling,
	title = {Smelling faults in spreadsheets},
	booktitle = {Proceedings of the 30th IEEE International Conference on Software Maintenance and Evolution},
	volume = {14},
	year = {2014},
	month = {September},
	address = {Vitoria, Canada},
	abstract = {<p>Despite being staggeringly error prone, spreadsheets are a highly flexible programming environment that is widely used in industry. In fact, spreadsheets are widely adopted for decision making, and decisions taken upon wrong (spreadsheet-based) assumptions may have serious economical impacts on businesses, among other consequences. This paper proposes a technique to automatically pinpoint potential faults in spreadsheets. It combines a catalog of spreadsheet smells that provide a first indication of a potential fault, with a generic spectrum-based fault localization strategy in order to improve (in terms of accuracy and false positive rate) on these initial results. Our technique has been implemented in a tool which helps users detecting faults.To validate the proposed technique, we consider a wellknown and well-documented catalog of faulty spreadsheets. Our experiments yield two main results: we were able to distinguish between smells that can point to faulty cells from smells and those that are not capable of doing so; and we provide a technique capable of detecting a significant number of errors: two thirds of the cells labeled as faulty are in fact (documented) errors.</p>
},
	attachments = {https://haslab.uminho.pt/sites/default/files/ruimaranhao/files/icsme14.pdf},
	author = {Rui Abreu and J{\'a}come Cunha and Jo{\~a}o Paulo Fernandes and Pedro Martins and Perez, Alexandre and Jo{\~a}o Alexandre Saraiva}
}