It's one of the most mindboggling things (the publishing racket is perhaps worse) about academia that CS papers introducing an algorithm aren't required to publish their implementation, even though there necessarily seems to be one doing eg. simulation studies.
I don't really understand the rationale behind omitting the implementation. Maybe people write such crappy code that they're ashamed of publishing it. Or it's the more sinister scenario that the algorithm is actually crappier than the paper claims.
Or someone handwaved important things like having an information function be available (impossible, used only in proofs of correctness, way of estimating it is critical).
Or a key assumption on input was just mentioned somewhere in the depths of the paper.
Or a very specific way of measuring the result hides the deficiencies. (Similar to p-hacking or misusing stats in medicine.)
It's sounds like the paper you struggled with was designed to obfuscate the particular conditions under which its results were produced. This may be beause one of the authors thinks there's money to be made from the secret sauce, or because they're misrepresenting how broadly applicable the result is. Or because they're sloppy. Or all three.
At a certain point, you have to stop blaming yourself for not understanding the literature. Sometimes it wasn't meant to be understood.
I've found that many researchers are very open to questions via email, however. Most of the time I'll get a response that can clarify a thing or two.
I personally feel that researchers just need to be better writers though. Most of the time, the writing is just plain bad. Perhaps there needs to be a way to enforce a bare minimum in writing quality. Personally I wouldn't be surprised to see more researchers employ editors for themselves.
How long do you think it took the researcher to develop the idea? Probably longer than a few weeks. Even if they could have communicated better, it's still the case that you, a non-expert (my apologies if this is untrue, I am assuming based on the context), can decipher and implement the method in a few weeks!
I can always just fall back to gradient descent instead of the optimization parts of the algorithm I don't understand, but that impacts performance, and I got the feeling I'd spend hours implementing this only to have something which can't perform in real-time so I gave up. It was just a side project. It's frustrating after devoting weeks to this. Reading and attempting to implement a research paper in my own field is incredibly hard.
I feel like if research papers were written in a more accessible, less dry manner and specified details important to implementation, the world could be a better place. If it were easier to implement these things as side projects, you might have people experimenting with these things at home and then starting businesses out of them.