This isn't that surprising, at least based on my limited experience from reading computer science research papers. My experience has been that there's usually not enough information for you to implement something. Am I an outlier, or have others experienced the same?
I've spent hours/days/weeks implementing algorithms or data structures from journal articles. No, you're not an outlier. A lot of times they don't include source code, even in the age of Github. Certain details or assumptions are often glossed over, and often the wording of a crucial technical detail is extremely ambiguous. Sometimes the only way I'm able to successfully implement the algorithm/data structure is through sheer luck - i.e. stumbling upon some piece of information elsewhere that gave me the necessary insight to understand what the author of the journal article meant.
I mean, I can understand academic time pressure and everything, but not providing a link to source code in this day and age is almost absurd. At the very least, it certainly doesn't encourage anyone to actually use your research in industry.
E.g. I did my M.Sc thesis on methods to reduce OCR error rates, and when doing my research for it I came across it all the time. Even things like tiny papers describing simple thresholding functions for scanned pages would include a formula or two that in theory fully specified what they described, except that they'd manage to omit critical information such as values of essential parameters even in cases where giving the actual, working code would have taken up a few lines of text.
