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I assume the RedLaser barcode app uses something similar from captured video frames combined with data from the accelerometer, no?

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Barcodes are designed to be easy to decode. Even blurred, the 1 or 2 dimensional frequency information is pretty well preserved. If I needed to combine data from several blurred images of a barcode I'd extract the likely values of the barcode from each image separately and then combine those.

Does it make a difference on the technique used if the image is out-of-focus versus blurred by camera motion?

So long as the motion blur is a small enough angle/translation, the difference is only in the shape of the blurring kernel. The kernel will be circular or gaussian for out of focus, while a line or arc for motion.

In one dimension, you'll be looking at a slice (more accurately, a summed projection) of the kernel. Focus = guassian, motion = square wavelet (line) or irregular (arc)

I doubt it. Blind deconvolution is hard. I think they may use something like super resolution where multiple blurred pictures can be used to recreate a less blury picture (and this is significantly easier to do than blind deconvolution).

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