Eye-tracking Metrics in Software Engineering. Sharafi, Z., Shaffer, T., Sharif, B., & Gu�h�neuc, Y. In Sun, J. & Reddy, Y. R., editors, Proceedings of the 22<sup>nd</sup> Asia-Pacific Software Engineering Conference (APSEC), pages 96–103, December, 2015. IEEE CS Press. 8 pages.
Paper abstract bibtex 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.
@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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