I highly disagree with that. In machine learning for instance, it's very important to be able to check authors' claims because otherwise you can't know if they are lying or not, or if they cheated or not ("what do you mean we can't use our test data to improve our training process?")
Plus, you can't improve on what others did if they don't let you access their own code and dataset. "We got better results than previous works it seems, but we can't know for sure because maybe that's because our method is better, maybe that's because our code is better, we will never know." My ML approach is more efficient than yours because you wrote it in python on your laptop and I wrote it in C and spent a lot of time to optimize it, plus I have a faster computer. Yeah sure. That's not science.
Ideally, what we need is being able to 1) reproduce from scratch, 2) rerun the experiment with the code used (which has a lot of pragmatical advantages too).
In fact, I would argue that even the examples you are giving are not "reproducibility". Reproducibility means that if you redo it _from scratch_, you reach the same conclusion. If the conclusion is "this algorithm describe in this paper is 20+-10% better than the algorithm described in this other paper, in those conditions", then, ideally, what you need to do is to read the first paper and follow the explanation to recreate the algorithm, read the second paper and follow the explanation to recreate the algorithm, read the conditions and reproduce them yourself, and then, you check if you get a compatible conclusion.
As for improving on top of others, again, the scientific paper explains the algorithm, just apply the recipe in your personal implementation, and you will have the same result. Even better: if you don't, you may have found a bug that exists in their implementation, and you have made a scientific progress that you would not have obtained if you would have just cut-and-pasted their code.
But as I've said, the ideal is to have both. Still, the sentence that we reacted on as "not scientific because not compatible with reproducibility" is still valid. It is true that, in practice, the code is not very useful in science (it may be a bit useful, but not as crucial as some may think), and it is true that this does not lead to a reproducibility problem, because the goal of the concept of reproducibility is to guarantee the existence of _independent_ implementations to check if we reach the same conclusion.
But ideally you want both: the description of the procedure to rewrite an equivalent program, and the actual code that gave the results detailed in the article. This is happening more and more frequently, and this is a good thing.
If you follow discussions about how to comment code properly, you will see that an important thing to understand to comment code properly is the fact that your comment should not describe the code, but explain the code. In science, the explanation is a very very very important part of what the community wants. The fact that this distinction exists for comments is the proof that "just the code" is not enough.
Then, yes, of course, it does not hurt to give the code. I have NEVER said otherwise. But just re-read the discussion: my point is that, in practice and in reality, the EXPLANATION is way more important than the description in scientific research, and, because of that, the scientific community is way more interested in discussing the explanation rather than the description (not that it is 100% useless, the same way that discussing plenty of other things is not 100% useless).
> ... reproducibility is at stakes.
True. But in this case, trying to solve that by giving the code is the worst way of solving reproducibility. If the EXPLANATION is not well done, than the science is not there. If you can't reproduce because you don't have a good explanation, than, the solution is to fix the explanation, not to give an unexplained code. Describing the code will NOT fix that, but will let bad science being used ("well, I have the code. I don't know exactly why they have done like that, but I can run the code, so let's use it")
> But ideally you want both: the description of the procedure to rewrite an equivalent program, and the actual code that gave the results detailed in the article. This is happening more and more frequently, and this is a good thing.
No one so far in this discussion disagrees with that. If I was not trying to strongly give the benefit of the doubt, I would be tempted to conclude from this discussion that this disproportionate reaction to just "they are not interested in the code" is from few persons who are totally oblivious of how science works, but are somehow triggered by the idea that the code is not the most important thing in the scientists eyes.
It just comforts me in the idea that some computer scientists have no idea of what are the tensions when doing science (some computer scientists, not all) and just refuse even to consider that maybe it is simply slightly different.
Cool. Except they don't give you the source even when the paper is about the source. So if you want to make sure their benchmarks make sense you can't.
How do i know? It has happened to me.
> You clearly have no idea what you are talking about. Therefore, your conclusions are worthless.
I'm sorry by being right I've offended your sensibility to the point that you need to insult me to feel whole again.
Something happened to you. But it is not a "reproducibility problem".
I guarantee you, at CERN, several teams, and several experiments, reproduce the results without sharing the code. The Higgs boson was observed with 5 sigma of statistical significance, by Atlas AND CMS, and they did NOT share any code.
How do I know? It has happened to me.
The problem of reproducibility is not about sharing the code. If the paper does not provide a complete explanation and does not have the code, you will not be able to reproduce it. But if the paper provides a complete explanation and does not have the code, you will be able to reproduce it. Worst, if the paper does not provide a complete explanation and provide the code, you will NOT be able to reproduce the experiment: you will be able to re-run the code, including the part of the code that contains unsound hypotheses, incorrect equations, and ill-advised choices, without having the elements to understand why those things should not be like that. If you have the elements to understand "wait, this code should not do that", then you have the explanation that allows you to rewrite some code from scratch without needing the code in a first place.
> I'm sorry by being right I've offended your sensibility to the point that you need to insult me to feel whole again.
Sorry if I offended you. The fact that you have no idea of what you are talking about is the result of an observation: you truly don't understand the concept of "reproducibility in science". It is not an opinion, it is a demonstrated fact: I have given real life example where reproducibility is achieved despite not having used the code (for example, the reproducibility of the observation of the Higgs boson despite the code not being shared), while you argued that the lack of code is a problem for reproducibility.
The part on the conclusions being worthless is a simple logic consequence: if you base your premises on incorrect understanding, then your conclusion should be discarded.
Sorry if you became so emotional that you were unable to read a simple observation and logic statement without imagining it was a personal attack.
Maybe studying very small particles made you forget about the rest of the world?
First, the CERN example was a counter-example. If you say "A implies B" and that someone shows an example where A implies B, it does not matter if this is just one example, it still demonstrates that your affirmation is bullshit.
Second, you cannot just say "let's just pretend that the rest of the world just works like I want. See, I'm therefore right". If "cern" is just a part of "science", then, it's YOUR JOB to give me the demonstration that the rest of science is different. Until then, your affirmation is the one who is pseudo-science.
Until now, all we have is, on one side, someone who has experience in science and who has provided a mechanism to explain why your affirmation is bullshit + a specific counter-example. And on the other side, someone who has just made some big affirmation with nothing below it. Sorry, but I'm pretty sure that everyone can see that you have absolutely nothing to defend your affirmation that was just motivated by a childish "I'm a computer scientist, so my methods are the best, and I'm offended that someone can say that these methods are great in many cases but not in all, so I will invent reasons to pretend they are somehow wrong"
It looks like you don't understand the definition and the point of reproducibility. If you just click on a button to recompute the results from the same code, this is not "reproducibility". The point of reproducibility is to have other scientists able to confirm your results in a fully independent way. They should be able to do it from scratch, without your code, and reach the same conclusion.
Using the code is therefore against reproducibility: people who use the code are not reproducing the experiment.
It is not restricted to the code. At CERN, the Atlas experiment and the CMS experiment are designed to be able to observe the same phenomenons, in order to bring independent measurements. Because of the notion of independence and reproducibility, while working in the same building, there are strong instructions to not share any non-published details with the members of the other experiment. The reason is that if there is an error in the reasoning, or if we observe a statistical fluctuations, or if there is a bug in the code, when the other experiment comes up with their results, their results will be unbiased.
Additionally, it is good practice to have several team doing their analysis in parallel on the same subject, each using their own code. This is called "cross-check analyses" and is a very important scientific procedure that is able to discover code bugs way more efficiently than unit test or code review.
> but you don't give them out
Why do you say we don't give them out? The code is available to reviewers. It's on the collaboration git repository and anyone in the collaboration can check it out.
They are not interested in that the same way they are not interested in the schematic of the Intel processor that was used in the laptop of the person who run the algorithm.
They are, however, interested in understanding deeply the reasoning and the logic that led to the conclusion, to the point that, if they want, they can rewrite their own code (in any language they want) and reach the same result. They don't see the code (not because they can't, but because they are smart enough to understand what reproducibility means), but they know what the code is doing.
> It's all very unscientific and uncooperative really. Let's not pretend it's "science"…
You clearly have no idea what you are talking about. Therefore, your conclusions are worthless.