Exactly. In one recent case, someone published a paper about an interesting graph centrality metric that I was interested in trying out. Unfortunately, their description in the paper was far too vague to be useful - "implemented as a simple extension of Brandes' algorithm". In attempting to reproduce it, that meant I needed to go read up on the algorithm they extended, and then try to figure out how they actually extended it. In the end, I couldn't actually reproduce the work, and never heard back about the code that the authors used in their published work. That severely degrades the utility of the paper. Yes - the paper does contain some knowledge that they shared with the world, but it was difficult to build upon and replicate since they failed to describe what amounts to the experimental apparatus and setup that was used to obtain the results they published. Unfortunately, this is relatively common in CS (at least, the corners of CS where I work).