Eye tracking is an increasingly more popular research method in software engineering and can be used to study how programmers process and comprehend source code. This study investigated the possibility to perform such studies remotely with the use of eye-tracking algorithms and consumer grade webcams. A practical experiment was set up to remotely gather gaze-data from programmers. Several processing steps were applied to the gaze-data to establish the adequacy of the procedure. Two main problems with the webcam eye-tracking technology were found. The first was the lack of a fixation detection algorithm developed specifically for low frequency webcam data. This makes isolation of eye-movements more difficult and the results possibly unreliable. The second was the lack of support for dealing with head movements when predicting the gaze-position. Online experiments are unsupervised and there is no guarantee a subject will keep their head still even if instructed to do so. This was thought to be the reason behind spatial shifts observed within the collected datasets. Positive trends in the data were also identified. Like the consistent dispersions of gaze-points, and certain recognisable reading trends. While deemed unsuited for the task. Ultimately, the positive trends provided optimism for the technology to be usable to study code reading in the future.