<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Abreu, Rui</style></author><author><style face="normal" font="default" size="100%">Cunha, Jácome</style></author><author><style face="normal" font="default" size="100%">Fernandes, João Paulo</style></author><author><style face="normal" font="default" size="100%">Martins, Pedro</style></author><author><style face="normal" font="default" size="100%">Perez, Alexandre</style></author><author><style face="normal" font="default" size="100%">Saraiva, João</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Smelling Faults in Spreadsheets</style></title><secondary-title><style face="normal" font="default" size="100%">Proceedings of the 30th IEEE International Conference on Software Maintenance and Evolution</style></secondary-title><tertiary-title><style face="normal" font="default" size="100%">ICSME '14</style></tertiary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Faults</style></keyword><keyword><style  face="normal" font="default" size="100%">Smells</style></keyword><keyword><style  face="normal" font="default" size="100%">Spreadsheets</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2014</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">\url{http://conferences.computer.org/icsme/2014/papers/6146a111.pdf}</style></url></web-urls><related-urls><url><style face="normal" font="default" size="100%">https://docentes.fct.unl.pt/sites/default/files/jmc-cunha/files/icsme14.pdf</style></url></related-urls></urls><publisher><style face="normal" font="default" size="100%">IEEE Computer Society</style></publisher><pub-location><style face="normal" font="default" size="100%">Washington, DC, USA</style></pub-location><pages><style face="normal" font="default" size="100%">111–120</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;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 well-known 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.&lt;/p&gt;
</style></abstract><notes><style face="normal" font="default" size="100%">&lt;p&gt;n/a&lt;/p&gt;
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