@INPROCEEDINGS{Sharafi15-APSEC-EyeTrackingMetrics,
   AUTHOR       = {Zohreh Sharafi and Timothy Shaffer and Bonita Sharif and 
      Yann-Ga�l Gu�h�neuc},
   BOOKTITLE    = {Proceedings of the 22<sup>nd</sup> Asia-Pacific Software Engineering Conference (APSEC)},
   TITLE        = {Eye-tracking Metrics in Software Engineering},
   YEAR         = {2015},
   OPTADDRESS   = {},
   OPTCROSSREF  = {},
   EDITOR       = {Jing Sun and Y. Raghu Reddy},
   MONTH        = {December},
   NOTE         = {8 pages.},
   OPTNUMBER    = {},
   OPTORGANIZATION = {},
   PAGES        = {96--103},
   PUBLISHER    = {IEEE CS Press},
   OPTSERIES    = {},
   OPTVOLUME    = {},
   KEYWORDS     = {Topic: <b>Program comprehension</b>, 
      Venue: <c>APSEC</c>},
   URL          = {http://www.ptidej.net/publications/documents/APSEC15.doc.pdf},
   PDF          = {http://www.ptidej.net/publications/documents/APSEC15.ppt.pdf},
   ABSTRACT     = {Eye-tracking studies are getting more prevalent in 
      software engineering. Researchers often use different metrics when 
      publishing their results in eye-tracking studies. Even when the same 
      metrics are used, they are given different names, causing 
      difficulties in comparing studies. To encourage replications and 
      facilitate advancing the state of the art, it is important that the 
      metrics used by researchers be clearly and consistently defined in 
      the literature. There is therefore a need for a survey of eyetracking 
      metrics to support the (future) goal of standardizing eyetracking 
      metrics. This paper seeks to bring awareness to the use of different 
      metrics along with practical suggestions on using them. It compares 
      and contrasts various eye-tracking metrics used in software 
      engineering. It also provides definitions for common metrics and 
      discusses some metrics that the software engineering community might 
      borrow from other fields.}
}

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It also provides definitions for common metrics and discusses some metrics that the software engineering community might borrow from other fields.","bibtex":"@INPROCEEDINGS{Sharafi15-APSEC-EyeTrackingMetrics,\r\n AUTHOR = {Zohreh Sharafi and Timothy Shaffer and Bonita Sharif and \r\n Yann-Ga�l Gu�h�neuc},\r\n BOOKTITLE = {Proceedings of the 22^nd Asia-Pacific Software Engineering Conference (APSEC)},\r\n TITLE = {Eye-tracking Metrics in Software Engineering},\r\n YEAR = {2015},\r\n OPTADDRESS = {},\r\n OPTCROSSREF = {},\r\n EDITOR = {Jing Sun and Y. Raghu Reddy},\r\n MONTH = {December},\r\n NOTE = {8 pages.},\r\n OPTNUMBER = {},\r\n OPTORGANIZATION = {},\r\n PAGES = {96--103},\r\n PUBLISHER = {IEEE CS Press},\r\n OPTSERIES = {},\r\n OPTVOLUME = {},\r\n KEYWORDS = {Topic: <b>Program comprehension</b>, \r\n Venue: <c>APSEC</c>},\r\n URL = {http://www.ptidej.net/publications/documents/APSEC15.doc.pdf},\r\n PDF = {http://www.ptidej.net/publications/documents/APSEC15.ppt.pdf},\r\n ABSTRACT = {Eye-tracking studies are getting more prevalent in \r\n software engineering. Researchers often use different metrics when \r\n publishing their results in eye-tracking studies. Even when the same \r\n metrics are used, they are given different names, causing \r\n difficulties in comparing studies. To encourage replications and \r\n facilitate advancing the state of the art, it is important that the \r\n metrics used by researchers be clearly and consistently defined in \r\n the literature. 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