text:
Professor I am working with asked for my code
My postdoctoral adviser has a colleague (another professor) who she collaborated with occasionally. This professor has data that I was interested in. Together with my advisor, the three of us started a project for which I did all the modeling.
We have not finished the project yet, but the 'other professor' announced today that he will be moving to another university in the next six months or so (I am not sure exactly when). He asked me if I could share with him a copy of the source code that I wrote for the modeling and analysis of the data. I feel uncomfortable about this, since I don't know if I will be included on manuscripts, new projects, etc. that will be coming out of the current unfinished project. I talked to my postdoctoral advisor, but she is not very helpful and actually suggested to 'just give him a copy of the [source code]'. I am not against sharing code, but I am just afraid this other professor will be using (a modified version of) my code and then not include me on a any manuscript that will be resulting from the code.

Do you have any actual reason to presuppose that the 'other' professor intends to cut you out?

Could you clarify your concerns? Are you thinking that the other professor would finish the current project without giving you credit?

@avid: I don't have strong relationship with this person. All communication was through my advisor.

@Daryl Bagley: Yes, exactly this (no credit, because I already finished all the code, so no need for the 'other professor' to keep me in the loop. I have seen it happen where people are involved early on in the process and contribute substantially, but then, a year or so later, they are not on the paper draft.

Are you sure that any products from the code would earn you authorship? I'm not sure it's guaranteed

Is the code in some repository such that you can prove that you had written it by some specific date? Is it even your code, if you were writing it when, in some sense, employed?

@AndrewMorton That is not a bad idea. I could put the code on GitHub to at least demonstrate ownership.

Did your collaborator mention why they actually need the code?

I see three productive suggestions in other comments and answers here so far:

Post your code on github (maybe shared only with collaborators until publication).
Add a license.
Have a specific conversation about authorship.

You should do all of these.
On the other hand, I also see suggestions you should not take, so I'll throw in these extra suggestions for what you should do instead:

At every moment, treat everyone as reasonable and level-headed.  Be assertive, but not aggressive.  Your goal is to resolve any dispute, rather than escalate hostilities, so don't start off with legalistic talk of how you could prove things in a court of law.
Continue making yourself valuable to the project.

I publish pretty much all of my code openly on github, even while I'm still working and haven't yet published.  But I have to say that if the goal is to get authorship on resulting papers, this alone can be counterproductive.  In my experience, many researchers will actually perceive making software open source as encouragement to use your software without bringing you in as an author, because they believe you're satisfied with a simple citation.  Of course they'll cite you properly, but you won't be an author on their paper.  I consider this a net benefit, but it's not what the OP seems to be looking for.  Github is very helpful for collaborating, and likely to be great for your career, but it's not enough to achieve the goal of authorship.
Similarly, most licenses put no particular academic obligation on the user.  As others have pointed out, there are plenty of good reasons to use a license.  But authorship is not one of them.  See this question for some good points on this topic.  Not having a license at all is certainly a bad idea.  So I encourage you to license and post your code.
But if you want to be an author, there's really no substitute for having an actual conversation about it.  Your advisor should be willing to discuss this specifically with you, and with the other prof.  You could broach the topic first with your advisor as a discussion about what sorts of work merit authorship on papers — which could help guide your academic plans anyway.  Your advisor will have a broader perspective about this topic generally, as well as specific insight into just how much work you've done.  It may turn out that your advisor realizes that you've done a great deal of work, and just assumes that you'd get authorship — so your goal is just to get explicit reassurance of this fact.  Or it may turn out that what you think is a great deal of work isn't actually that significant, and you would be better served by spending your time on other projects (I only say this because your question is not clear; I really don't know).
Most of all, this work is almost certainly not of the variety that you need to entertain daydreams about this ending up "in a court of law", or requiring "juriprudence-tested" [sic] evidence, as one comment suggested.  If this is patentable software, you should talk to your institution's IP office.  Otherwise, this just isn't going to be such a big deal.  Lawyers will not be getting involved.  The very most dramatic scenario I can imagine involves some ombudsman or editor looking into this, and they'll take you at your word that the git commit dates on github (which could be faked, in principle) are honest — because they'll come into this assuming that any disagreements are at least honest disagreements, and that no parties will be fabricating evidence.
In the same way, you should go into these conversations assuming good faith.  It's important not to go in "guns blazing", and ready to escalate what could have been a friendly and productive exchange into a fight.  Remember that the other prof is only leaving your institution, not defecting in a war.  You can stay friends and collaborators, which will be to your benefit.  Be prepared to assert yourself, but at every point in the dialog take the position that you're just seeking clarification and trying to settle minor details amicably.  If you bring up the fact that you could prove your contribution to objective third parties — when there's almost certainly no need for such a thing — you could be shooting yourself in the foot, because you're suggesting that this is a hostile situation, which could induce the other prof (and maybe even your own advisor) to just drop the project as more trouble than it's worth.
I think it would be entirely reasonable to let your advisor know that this is causing you some anxiety, and even say to her what you said in a comment above: "I have seen it happen where people are involved early on in the process and contribute substantially, but then, a year or so later, they are not on the paper draft."  This is a reasonable concern, and you have a right to ask for clarity.  But the other prof has a right to be treated like a reasonable and ethical person.
Finally, after sharing the code with the other prof, it can be helpful if you try to engage, rather than just crossing your fingers that you eventually get an email informing you that you're an author.  Ask questions, and offer to do some additional analyses.  Start talking about the paper(s) that you're expecting to come out of this, and generally try to maintain the collaboration as an active one.  If you make yourself valuable, people will be clamoring to have you as an author.

FYI: if you choose no-license then you are actually screwing yourself AND the other person... because no-license is equivalent to full-copyright (aka no-permission) and is MOST restrictive (sources: here and here). "When you make a creative work (which includes code), the work is under exclusive copyright by default. Unless you include a license that specifies otherwise, nobody else can copy, distribute, or modify your work"

This. Said what I wanted to say in my response, but much better, plus several other things, too.

"Most licenses put no particular academic obligation on the user." IMHO this is as it should be also from an academic point of view. The obligations to properly cite or include as coauthor aridr independently from the question of license. E.g. even an institute owning some software (as opposed to having a license) has these obligations.

@cbeleitesunhappywithSX Just to be clear, that's what I'm saying.  Adding a license is good for other reasons (e.g., sny1kk's point), and should be done anyway — but is not sufficient for the OP's goals, despite what others suggested.

You seem uncomfortable sharing interim results with  collaborators. That goes against the collaboration spirit and I implore you to share all results. In the future, don't start a collaboration with anyone who you aren't willing to share interim results with.

I am just afraid this other professor will be using (a modified version of) my code and then not include me on a any manuscript that will be resulting from the code.

You are afraid this other professor will commit academic fraud, steal intellectual property, or both, seemingly without any basis for concern. Again, I implore you to share all results. (Although I think it is unnecessary, you could defend against this other professor by making interim results available online.)

Read the comments, they are excellent.

It's also worth noting that not wanting to share the code implies (a) you suspect that this professor plans on committing fraud and (b) you don't think that the professor wants to know how the work was done on a paper for which they will have their name on. This is quite pessimistic.

if you are still uncomfortable with sharing your code after these answer. then i recommend licensing all your code (for example: GPL v2 or GPL v3) to protect yourself and ensure sharing in the future.

if you choose no-license then you are actually screwing yourself AND the other person... because no-license is equivalent to full-copyright (aka no-permission) and is MOST restrictive (sources: here and here). "When you make a creative work (which includes code), the work is under exclusive copyright by default. Unless you include a license that specifies otherwise, nobody else can copy, distribute, or modify your work"

@CliffAB I get a), but not b). If he has the code, he can just read up on what has been done.

@NickDewit: my point is that if a collaborator isn't allowed access to the code, they can't check that the code does what they think it does. In most cases it'd be pretty pessimistic for a collaborator to be okay with that (other than they do the non-math/code part of the research and just trust you since it's not their area), as that implies not really caring about the work.

It's unlikely a professor will risk their entire career for your piece of code. I'm not sure who you think you are, but the likeliness of that happening is very low.

If the comments are excellent, please make sure they're stored in an answer. Any answer. Comments come and go, answers are forever (thanks to revision history).

@Mast I seem to recall being previously admonished for doing so...

I think you are missing one point. Many scientists use commercial (black-box) codes in their work. The codes are protected by licenses and you have no access to the source. Bad for science, bad for reviewing, but still tolerated. @CliffAB As for the fraud, that not need to be an obvious one. You can just save a couple of month by reusing some pieces for other project, and just get a priority. This is just unverifiable!

@user2768 the entire point of comments is to suggest improvements to the answer. In the best of worlds, we wouldn't have any comments because they would all be removed as the answer is edited to respond to their input.

@FerventHippo I don't disagree. Yet, I seem to recall being accused of misbehaviour for including the words of others, rather than simply referring to their original words. (Of course, this could be avoided by improving my answer based upon the words of others, but quite frankly, that's an additional burden and others have already stated things rather well.)

@yarchik I'm promoting good science and ignoring bad science.

I've often collaborated with people at other institutions, and I would expect to always see all code which was used in any paper I was an author of.
If one of my collaborators refused to show me their code, my assumption would be there was something badly wrong with it. I would certainly refuse to publish any work with that person, as I would have no way of knowing my name wasn't being placed on a paper with serious issues.

I might assume there was something wrong with them, not just the code.

In principle, I would have agreed. However, since I have met a few people that have been played by external players (basically, provided material and code) and found that they have been scooped, results published, and/or mentioned without attribution and proposals written based on them without the original person even included, I find this response too absolutistic.

As @CaptainEmacs says, I’ve known some people who are a bit paranoid because they’ve been treated badly in the past.  “Once bitten, twice shy.”  If a collaborator is mistrustful, that’s unfortunate, but it’s better to respond by trying to build trust with them, if they’re otherwise interesting to work with.

I strongly suggest two things.
First is that you share the code. Absolutely. Even offer to extend it as required.
Second is that you arrange with the other two people that you will continue to collaborate on this, and future projects, as long as you live.
If you don't do these things and generally try to lock up what you do, your career will be sub-optimal. Perhaps not dead in the water, but less than it could be.
Knowledge isn't like gum-drops. We can share it and still keep it. In fact, sharing it makes it grow. If your reputation is one of stinginess then no one will want to share with you and the data (from that other person) wouldn't have been available to you to even begin to work with.
Having a circle of collaborators is a powerful thing that will carry you over the hard spots in your career path.
The only exception to this is if you had prior evidence that the other person is already known to plagiarize and to not give proper credit.

Personal note: Over my career I developed many continuing collaborative relationships with others at other universities and in other countries. We got a lot done together that it would have been hard or impossible to do alone.

What do you mean by "as long as you live"? The OP should now decide to work for their whole life together with them? (I guess that's not what you mean, but what do you mean?)

@user111388: Yes, that is what I mean. Establish a very long-lived collaborative relationship with them. Get absorbed into their circles of collaboration and absorb others into yours. Of course it may be impossible, but take that as a goal.

This is a good strategy even just from the point of view of ensuring co-authorship. An active collaborator who is involved in the project, writing the part of the paper that explains the modelling, making changes to the code if that will help with the analysis etc. is very unlikely to get forgotten when it comes to the author list.

Now, I would not be so quick to judgement as many here. I can understand the sentiment, and indeed code-sharing is an important, foundational part of most software developers as a vague community.
HOWEVER, I've experienced some issues where out-of-faculty instructors did off with some code for commercial purposes. I wouldn't say it's very common, or that you need to be highly paranoid about this, but there's a very simple solution to your problem.
Just publish your code on GitHub with an Apache 2.0 license.
Then send them the link.
Tada.
You have credit, you have access, your future contributions live somewhere with citation. It'll be fine. If you really want you can even make the repo private unless something foul goes afoot.

Came here for this answer. The OQ doesn't have a sharing problem, but rather a licensing problem. That means it needs a licensing solution. If they still try to use it without attribution, you've now made it quite clear up front what's legal/ethical use and what isn't. (However, your university may hold copyright interest in your work, as might any actual collaborators. Look into that).

I was reading the answers before giving mine - which would be exactly the one here (+1): sharing on a public, open platform. I do not know which license is the best but the fact that you publish it under your name gives you authorship. It is hardly possible afterwards for someone to claim the work as theirs.

I would probably refrain from making the repo private: it may be that the action of making it public is timestamped somewhere and it just blurs the lines. If you publish your code privately on 1 APR 2020 and the problem appears on 12 SEP 2020, and some time stamp shows that "the repository was blah blah made public on 25 SEP 2020", one can read this as you coming late (your code is from the 25th while the issue is on the 20th)

@WoJ indeed i don't recommend publishing privately either, but sometimes there are issues where teams want to keep code between themselves until publish. given the somewhat fringe nature of the question i just thought i'd mention the flexibility

Clearly you do not know the other prof well enough to trust them.
In such cases, clarify authorship agreements ahead of time (authorship, number of papers; with lower priority, order of authors, but probably that should be left for later). If satisfactory, proceed to share. The danger lies always in implicit assumptions about who gets what type of attribution in which papers.
Much of that danger can be mitigated by an open, but friendly conversation on how the credit attribution is going to look.

Once there was an invention, by British amateur chemist and hairdresser, of intumescent material claimed to be able to withstand and insulate from extreme heat, named Starlite. Starlite was proven to be able to withstand attack by a laser beam that could produce a temperature of 10,000 degrees Celsius. It would also prevent a blowtorch from damaging a human hand.
But Starlite's composition was a closely guarded secret. The inventor allowed various organisations such as the Atomic Weapons Establishment and ICI to conduct tests on samples, but he was scared and did not permit them to retain samples for fear of reverse engineering.
He maintained that his invention was worth billions. But as he died in 2011 he took the secret recipe to the grave. Still today there has been no commercialisation of Starlite, and the formulation of the material has not been released to the public.
So there was this incredible material and a selfish scientist, whose egocentrism made him value the greater good of humanity much less than his own bussiness. And there is your code and you, but it is almost certain that you vastly overestimate the greatness and usefulness of your own code and it is not going to make any Starlite-like potential breakthrough in rocket science. So you should share the code without a second thought, as collaboration is essential in academia. And if you can't drop your big ego, maybe academia just isn't a place for you.

I wouldn't call someone who doesn't share a billion dollar receipe "selfish". After all, when explaing people that people who promise "with this trick you earn 1 million dollar easily" are scams, the most common argument is "why would anyone who know such a secret trick would share it instead of keeping the money"?

Cool story! Here’s a Wikipedia link for those who wish to learn more about it.

@HowardBarnamax Somehow I do not get the argument here. He didn't publish, and said it's worth billions - so it sounds like he wanted (but didn't succeed) to commercialise. Is commercialisation selfish? Should he just have published this for free? I do not understand the link to OP's question in a commercial case.

Both the inventor and his family say that the recipe was not lost, but left with close relatives. The story of how he failed to commercialise it is a long and complicated one.

@Captain Emacs My point is that even a genuine "billion dollar idea" is effectively worth $0 if it is never properly executed. And yes, he was selfish because any advanced science research is too complicated to be done without collaboration in a basement. He could have dropped his big ego and collaborate with scientists, which at least had the chance of making him rich. But he had wrong, ill mentality of assuming negative intentions of the rest of the world, paranoid feeling that any moment he could be tricked/cheated and he haven't seen a single cent of his claimed "billion dollars".

@HowardBarnamax Quite possible that he had a so-called "big ego", there are people like that, many of them crackpots, some rare of them genuine geniuses. But perhaps it was his priority not to be taken advantage of rather than making someone else rich. Not everybody is as selfless as Charles Goodyear. It is infuriating if someone else makes away with your idea. It happened rarely enough to me and I know to protect myself well enough to remain trusting, but others were not so lucky. I know people with whose know-how others made a career, while themselves were not able to cash it in.

I talked to my postdoctoral advisor, but she is not very helpful and actually suggested to 'just give him a copy of the syntax'.

Your postdoctoral advisor is right: you collaborated on this work so you should be happy to share it.
Think about it this way: a lot of academic software ends up being open source; what makes you treat this collaborator differently than you would a future researcher who wants to use your work? The difference here is that you may not have published yet, but I wouldn't be afraid to just post the syntax online. You should not be worried about being scooped; your goal is to get people to be interested and aware of your work; if they go so far as to use your code, that's even better.
Academia is a lot different than industry where one is always worried about company secrets and intellectual property. In academia, we care about attribution, not ownership. Since the person who really had this idea (wrote down the code) is you, you should be recognized and the code should be attributed to you. But that's different from saying that you own the idea and no one gets to use it, which is contrary to the spirit of research, particularly when this professor is involved in the same project as you.

By the way, when you share the code, if it makes you feel better you can ask them about how they plan to use it. You can also put a record that the code was yours (e.g. publishing it online right away). These are ways to cover yourself in the event of academic misconduct, and to keep yourself in the loop. As you are the one who wrote the code, just as they have a right to see it, you have a right to know how they are planning to use it going forward.

If the prof can use your code without using you, then either the code is simple, or he will soon understand that he needs you.
I suggest to not fear the code. Fear the idea what is behind it.
Note, the prof has far more to lose by a plagium accusation than the time of re-implementing the code, but not this is the case for the idea behind it.
A prof wanting your code is not a danger, he is a chance. If he is going to another university... would you like to go with him? Would you like to join him a decade later?
Think also about the LoRs you will might to get from him in the future.
So, don't fear the code. Watch the papers of the prof - and have a good contact with him. He can become extremely useful for you in the future.
The likely cause of the reaction of the postdoc advisor is that he sees the same, but he can not say it to you - and he will retire from where you are now.
P.s. If the prof hears back that you have this problem, yes that will become a danger.
P.s.2. As other answer says, open-sourcing the code could make it an excellent reference for you in the future.

if it quacks like a duck... you got a bad feeling obviously already from the get go, so what is the reason for that? Obviously you went through the trouble of posting on this forum/board, so that tells me it means more than "no big deal". Attach a disclaimer citing Intellectual Property Copyright [date you created version 1] and include it in as a comment header of the source. Post it in a repository if you want and then collaborate as you originally intended to. GNU Not Unix...heh. Libertarian way, it is good to share, so far as that it does not impede upon the rights of an individual, including yourself. You have every right to be concerned, but you also agreed to work as a team. So do both, and next time trust your gut, in the end it is all you got.

I generally agree with your answer, but at the same time feel like these jokes about quacking ducks and Lunix systems, which I don't even understand, are completely unneeded and out of the place. Hermetic IT humor should stay at IT and not leak to normal outside world. It makes no wonder why IT people are given the reputation of socially inept, awkward and creepy weirdos.

I am an IT guy, and I am quite socially inept, awkward, creepy and weird. I also support Linux (even the non-GNU ones :P) and open source in general. '''Even so''', I found @Walter Marks' answer to be pedantic and infuriating. I don't have enough score to downvote it, but I surely would.

Don't hide your assets under a bushel. You want to establish a career where you are valued for your expertise, knowledge, and insight. To do that you need to establish a reputation, and the best way to establish a reputation is to be generous in sharing your knowledge. The more you give away, the more people will come to you wanting your services. By contrast, if you establish a reputation for being unhelpful and reluctant to contribute to the community, the less people will want to work with you.

Given the nature of human beings, you are right to be skeptical. No one is going to look out for you except you. It comes down to ownership. Is the institution you are at now aware that this guy wants to take intellectual property paid for by their institution to a different institution? I would go up the ladder and make sure you get clearance from someone that it is okay to allow this person to take your work elsewhere. Colleges are in competition with one another despite what those in academia like to admit. You might find yourself in hot water if it turns out this guy goes somewhere else and publishes his work giving the new institution credit.
All of these answers suggesting you capitulate in the name of charity are hogwash. Follow your gut. Don't let people steal your success or try to guilt you out of it in the name of obedience or subservience to the collective.

The immediate downvotes are exactly what I expected and should illustrate precisely the point I am making about your instincts, Nick. Academia expects you to walk in lock-step and put the collective over the individual. Protect yourself and your work. Do not get cheated or bullied out of it in a atmosphere where accolades and credit are the only currency.

Collaborators should provide assistance that cannot be obtained another way.  Collaborating increases your competitive advantage.  If collaborating is decreasing your competitive advantage, you are doing it wrong.

I agree. Collaboration is a two-way street but equity often isn't. Professors all too often take advantage and credit for their underlings' work without providing anything in return. If the people you're collaborating with have a reputation for fairness and give you the impression that they are reciprocating equitable value then personally, if I had the blessings of all interested and involved parties, I would share my work. But if I do not know someone and they made a demand of me as though they were entitled, I would be hesitant to comply simply because the demand would make me suspicious.

Not a downvoter. I think your answer makes a fair point, but also that the attacks to "those in academia" and the other answers are unnecessary at best. In fact I think you can remove the second paragraph entirely.

@AnonymousPhysicist: well, it depends. A great site to see it at work: https://ncase.me/trust/

That's an interesting simulation but as I am not an expert in statistics, my gut instinct after messing around with it for a few minutes is that it's selectively presenting scenarios to deliver specific outcomes. But certainly an entertaining and lighthearted look at generic personality types and harmless consequences. Thanks for sharing!

This answer demonstrates strong opinions about how academia should work, but little understanding of how academia does work.  First of all, h will not get "in hot water" for doing what his advisor directed in this situation; the advisor would be the one to take any heat — though even that is extremely unlikely.  Moreover, the other prof is still a prof at this institution, may be a co-PI, and might have some right to the code — denial of which is more likely to cause trouble.  The most likely result is that making a federal case out of every little thing would cripple the OP's career.

OP wanted feedback because he has a suspicion, and a right to the suspicion, that he's being ordered to hand over his work in exchange for ??? That he may or may not get into hot water for turning over something is just and\ opinion, as well (yours) and my advice is to be safe rather than sorry. You are generalizing academia same as you accuse me of except you are coming from an angle of naivety when it comes to human beings and their sometimes selfish motivations. The entirety of my advice was to protect the OPs own interests and follow his gut instinct. Sorry that offends you. Seems obvious.


text:
Question regarding post-doc salary and moving expense (US)
I'm a 2nd-year post-doc at a US university on the West coast, and I'm currently seeking my next position. I have had interviews at two universities on the East coast.  Because I received positive feedback and my interests align well with those positions, I believe that they will be offered.
Here're my question about the salary:

Do they (university and PI) usually consider the 2 years of my previous experience in my current school? Does US university faculties usually consider the previous experience?
If they do consider experience, then will my salary be calculated as for a 3rd-year postdoc?
If they don't consider experience, then how could I request a raise to 3rd-year post-doc level? Is it OK to negotiate regarding this issue?
I know that PIs (university professors) usually do not offer the moving expense for new post-docs. But is there any chance that the university might offer support with moving expenses?

I have never negotiated my salary before. There was no choice when I was Ph.D., and the first post-doc position offered to me was quite generous. So these kinds of things are totally new to me.

For my post-doc in the US (in Computer Science, funded on a NSF grant), the salary was not negotiable, and there was no reallocation funds. I had a small raise for the second year, though (it was an automatic, University-level raise). My experience made me hired, but did not impact my salary. There won't be a definitive answer to your question other than the one you'll get by asking. If you get an offer, you're in position to ask, but it's better if you can justify how this raise would help you in performing great in your work.

This may depend on the funding source/your field. Postdocs funded via certain NIH mechanisms have a mandatory salary minimum which varies by year: https://grants.nih.gov/grants/guide/notice-files/NOT-OD-17-003.html

In my experience, the particulars of a postdoc position vary more widely than academic jobs at any other level -- so much so that it may not be helpful to speak in generalities.
I have direct experience with (some) postdoc positions in mathematics in the United States and Canada.  For these postdoc positions, the salary was the same for all years (usually 2-3) of the position.  Moreover this salary was a standard one given to all postdocs of the same "kind" (roughly, the same funding source) and was not negotiated in the cases known to me.  However, if I remember correctly, the last time I brought this up on this site someone else told me of a North American math postdoc position that did include annual raises.
Again in my (relatively limited) experience, someone who does a second postdoc is not "senior" in any positive way to someone who is on their first postdoc -- if anything, there may be a mild perception that someone who is doing their second postdoc was not successful in landing a tenure track job.  But these things may be different in your field.

how can I 'politely' ask them to raise the salary according to 3rd year post-doc level?

The way to ask politely is...to ask, politely.  Namely, don't ask them to do it, but inquire into the possibility of doing it.  There is really no harm in asking about a salary bump, moving expenses or whatever -- if it's not on the table, they'll tell you.  If it is, you can explore it.  As long as you don't make hard demands or counteroffers, they should be happy to talk to you about it.

source: Stack Exchange

license: Creative Commons - Attribution Share-Alike - https://creativecommons.org/licenses/by-sa/3.0/

sort: votes


text:
How old can references or sources in a thesis be?
I have read that references in scientific papers should be no more than 2-3 years old, since such fields move fast, and no more than 10 years for arts or related fields:

A good rule of thumb is to use sources published in the past 10 years
  for research in the arts, humanities, literature, history, etc.
For faster-paced fields, sources published in the past 2-3 years is a
  good benchmark since these sources are more current and reflect the
  newest discoveries, theories, processes, or best practices.

However, I believe that's subjective, so how old is it for a reference to be "too old" to cite?

Here: http://libanswers.snhu.edu/faq/215024

"For faster-paced fields, sources published in the past 2-3 years is a good benchmark since these sources are more current and reflect the newest discoveries, theories, processes, or best practices."

@Roland strictly speaking you are right: as written the OP states that a publication must be older than 2 years before you can cite it. However, given the content of the question I suspect that the OP intended to say that a publication must be younger than 2 years.

I'm not quite sure whether the author of that page meant at least 2 years or within 2 years

No study is too old to cite, but not all studies "age well". Especially in fast paced discipline studies can easily be obsolete. However, this does not mean that all older studies in those disciplines become obsolete, just that many do. You can and should use those non-obsolete older ones.

Understood, thank you. Write that into an answer so I could accept it

If you are still allowed to reference Plato, that's more than 10 years...

I notice the web page you cited says "A good rule of thumb is" and "is a good benchmark", which is a lot softer than your wording suggests, especially in trying to pin-point the exact suggested constraints. Also, the librarian's answer clearly seems to be designed for undergraduate research papers and projects, and a quick check shows the university serves almost entirely undergraduates. Finally, a look at the "Related FAQs" titles on the right side shows the kinds of things (allowing for a 40 year gap) covered in my required freshman English composition course.

Can you put the link into the question?

Related if not duplicate: How can I tell if a paper is too old to be a reference for my research?

Maxwell's equations, Kepler's laws of planetary motion, Mass–energy equivalence? Nope, they're all much too old to be used in any serious research paper!

One horrible pattern I have observed is when people cite current-year papers for centuries old obvious common knowledge. It comes across as blatant citation count inflation, so don't do it.

So - if someone writes a paper explaining why Noahs flood never happened; are you saying they're not allowed to reference the bible?   Seems a little harsh to me.

The oldest paper I cited in my PhD thesis (in pure mathematics) is an article of Schur of 1890. Of course, in mathematics older papers remain true and relevant, while in other fields it can be different.

@Daniel Robert-Nicoud: I was curious about my PhD thesis, but I stopped counting after 18 entries from the 1800s, the last of which by Dini (i.e. in the D's). Earliest I saw was this 1806 paper by Ampère, but I was only searching for appearances of "18", so there might be a 1700s item in there. I'm pretty sure nothing in 1600s or earlier, however. (moments later) I checked a few name possibilities (e.g. Lagrange) and found this 1786 book by L'Huilier in the bibliography.

This rule of thumb is over 10 years old, hence too old, hence doesn't apply. Problem solved!

I am in a very fast moving field, but still when I submitted last year one of my  examiners complained that i cited very little from pre2006, in particular commenting that i didn't  reference any of the works from a particular conference in 1990.  I think the oldest paper i cited was from 1906, and a cited  a few from the 60s, but  indeed those  were the exceptions. I think the examiner's  complaint was fair. Even fast moving fields need background, and a  thesis unlike a paper is a place you have space to give it.

If this were a rule, would we be banned from decomposing matrices (first described in the 1870s), or using the Fourier transform (1820s)? And even if these examples are "trivial" enough to not warrant citations, many modern fast-developing fields in computer science started in the 1950-1960s, so the papers which started the whole discipline are worthy of mention for a few short sentences in the introduction, in many cases. In many cases you are solving a general problem, for which there are already special cases solved several decades ago. Why not mention them?

References can be as old as they need to be to cover the material.  I had some that were more than 30 years old. But if all of your references are "old," people are going to want to know why.
You must also be sure you cover the most current research in your field.  A few in my own dissertation were for material published in the same year as my own work.
The link given in the comments and the revised question seems to be directed toward undergraduate research assignments, and the "ten years" reference is a part of an example assignment, not a requirement given by the Shapiro Library. The key idea in the link is that references must be "somewhat current."
For a thesis or dissertation, one must cover the field, including both early and very new research.

Indeed, I suspect that when flipping through a typical issue of a typical journal in most any field, one will find several papers whose references include items listed as "to appear", or "forthcoming", or "under review", or "submitted", etc.

"References can be as old as they need to be" -- while I agree, the link the OP posted suggests that there are assignments saying "Sources must be published in the last 10 years".

@Ingo Well, yes, but that link seems directed at undergraduate research assignments, and in in fact, that "last ten years" bit is prefaced with, "If it’s a requirement for your assignment..."  For a doctoral dissertation, one is expected to cover the field.

Something worth mentioning might be the difference between referencing research results, where you want to try and have relevant recent material, and referencing ideas, which might predate their use in actual research. For example, In my Master's thesis I referenced a pre-1900 paper by Karl Pearson for an idea he discussed that was important for my research, but then referenced modern research papers for my actual implementation. Another example might be natural selection; depending on the context, Darwin is an obvious reference.

In physics it is not uncommon to cite a 60-100year old papers.

You need to have read that paper because some examiner WILL ask you about it.

When I was an undergraduate in the late 70's we were told about the Science Citation Index, and it was pointed out that "Newton, I" was still being cited.

A simple example: One sentence in a letter from 1961 said something I was trying to do couldn't be done.  That was the last published word on the topic (polishing calcite normal to the optic axis).  Of course I'd spent several weeks trying it before managing to find a source.

There is no rule about the age of citations. For example in my PhD-thesis I quoted some math-papers from 1600s that were originally written in latin (but those were exceptions).
Much more relavant than the year is the content of a citation and that you cover the relevant literature.
Also, you might want to include a few (relevant!) citations from recent years in order to show that you did your reading not just at the beginning of your thesis and then ignored everything afterwards.

In math it is common to cite old papers. 1600s is indeed exceptionally old but it is not uncommon to cite 10-100 years old papers.

I would say that it would be a bit unusual for a math paper to have most of its references under ten years old (unless the authors give only a very brief account of the context and there is only a handful of references in all).

@Yanko Ten years is old? Jeez, kids today. I doubt I've ever written a paper (including the ones I wrote more than ten years ago) that didn't cite something at least ten years old.

But did you really read those papers written in Latin?

I have cited a book on farming by Columella from the 1st century CE.
It provided crucial evidence for the use of a word at that time. But I did not take the evidence as the final say on the matter. I also cited 15th century academic analysis of the evidence as well as 21st century work. There is a fundamental difference between saying

It is true because X says so

and

X says so, so let us analyse it and cite more recent opinions on whether it is true.

In any discipline it may be necessary to contrast older and younger opinions on the same subject, and you will have to do some work yourself to argue that any given source, whatever its age, is - or is not - reliable.
As it happens, I rejected all the academic analysis and accepted my own interpretation of the original evidence. You as a researcher are expected to determine on a case-by-case basis what evidence needs to be cited, and what can be accepted.
Of course, at some stage, you have to accept that a certain claim is true because X says so. To do this you have to cite something that is fairly recent (which will depend on the discipline) and, if it not the most recent, argue why you are accepting it in preference to the most recent.

Your rule has a large fraction of exception that you should always consider. Make sure you cite the relevant papers for your claims and that you cite the papers which were the first introducing the idea. Don't cite a textbook for ideas just because they are recent. Instead, try to find and cite the original works.
If you cite an idea originating back to Aristoteles it does not make sense to use a recent source. The idea is that old! Also, if you want to prove your claim, that some method was used in the 70s, it's useful to cite papers written in the 70s.

This hits what I consider the key point. Each citation should be appropriate for its purpose. Documenting the origins of a question is different from documenting the state of the art in a rapidly changing research area.

The rule you quote is total nonsense for the sciences, and I have a hard time taking it seriously for the humanities.
You cite whatever you need to cite, regardless of its age. Typically, if you're referring to something that is decades old, it's now either common knowledge (e.g., Newton's laws) so probably doesn't need citation at all, or it's in textbooks (which are probably more appropriate to cite than the original source). Both of those things are a consequence of age but age per se is a completely spurious reason to not cite something.

In the humanities it's outright laughable. Besides the fact that often our sources are necessarily quite a bit older (classicists will quote stuff from antiquity, medievalists from the medieval, etc, historians from their period of history), many things we study may only be taken up by someone every few years or decades even, so to even do a cursory review of prior work you're going to be citing old stuff unless you're on a very popular topic.

@guifa That's what I figured, but I was waiting for somebody else to say it, since "Scientist guesses what the humanities are like" is probably pretty laughable, too!

A group of researchers published this very interesting paper:
The nearly universal link between the age of past knowledge and tomorrow’s breakthroughs in science and technology: The hotspot
From a pure data science perspective, they try to understand how the distribution of reference age affects the forward citations of an article. They analyze all publications (~ 28 million) in Web of Science published between 1945 - 2013.
Unfortunately, they do not show an aggregated histogram of age differences between a publication and its references. But in Fig. 1 we see the mean (0-50 years) and variance (0-4) for all published papers and it is all over the place. So the take away might be to cite what you want.
However, they echo in their paper the comments and answers that you got here. Impactful and hopefully good research seems to differ from the "cite what you want" approach. If you want to increase the likelihood of your work having an impact you should base your work on recent advances but also be aware of well-established theories or overlooked ideas from the past. They show this in the paper by finding a hotspot of highly cited papers that have a low mean age distance to their references but a high variance in age distance.
Here is a link to the paper (super interesting):
http://advances.sciencemag.org/content/advances/3/4/e1601315.full.pdf

There's no limit on how old they can be. In biology people often cite Darwin (1859) and geneticists who work on pedigrees can cite government records from hundreds of years ago. Work involving theology may cite the Bible. Historians cite original documents from thousands of years ago. Sometimes a fun game is to see what the oldest citation you can get away with is. Plato or Aristotle is often a safe bet.
Generally, you are supposed to cite the oldest paper that made a discovery, as the credit belongs to them. When in doubt, you can cite one old and one new paper.
However, your work must be in the context of contemporary scientific literature. If you cite a 50 year old paper for a theory, you better make sure the theory has not been disproven in another paper published 30 years after. If you say the state of the art in a field is a paper published 10 years ago, it would look really bad if somebody brought up a 5 year old paper that advanced it further. This is why citing old material is risky: You can't easily tell that it's still current. If a paper came out last monday, chances are pretty low that somebody refuted it in that time.

I'm sorry but this is terrible. You seem to be advocating not citing older work that you use, purely to avoid the embarrasment of being out of date. That's what you literature search is supposed to avoid. If you're using the 50-year-old theory, you need to cite something for it. If that theory has been refuted, you're going to look like an idiot whether you cite the original paper or not. If you're out-of-date on the state of the art, you need to find out what it really is. And that paper that came out last Monday also hasn't had time for anyone to check that it seems to be true!

@DavidRicherby I'm sorry but your comment is terrible. You seem to have confused a number of points. Notable among them is your mistaking numbers given as examples for actual universal rules. I'd recommend re-reading the post carefully. If you still have questions, I'd be happy to respond to them if you phrase it in a more constructive manner.

I've re-read your answer and I stand by what I wrote. I'm not criticizing the numbers at all. I'm criticizing what appears to be a recommendation to avoid citing old stuff because it might be out of date and your literature search might have failed to spot that. If that's not what you meant, what did you mean?

@DavidRicherby I didn't say to avoid citing old stuff because it might be out of date. I said that when citing old material, it is especially important to make sure it's not obsolete.

To be honest, just like you’ve said, all of this is quite subjective... Personally, I believe that if a paper is relevant to the point you are trying to make and hasn’t been categorically disproven then it’s fair game. However, what I think is irrelevant; it depends on the person marking your dissertation and how they feel about it. Some academics I know don’t care while others do. I was once marked down for using a 7 year old paper as a reference even though it was very relevant to my work, simply because the lecturer marking my work didn’t want to see anything older than 5 years.
For the most part, it should be fine. Academics who insist on only recent papers are few, in my experience.

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Difference between good and not so good university?
Here is my analysis for a theoretical subject like Math:
(Also assume I am super-smart which I am not):

I assume the stipend would be the same. So will the facility.
There is a change that a good university has a more accomplished professor. But since this is research, I can always go and meet him. Also, many schools allow having a guide from outside the university.
From my experience, the elite university always has a difficult curriculum along with some really book-smart students. So I would be really tensed to pass the exam and hence my research would suffer (Note here I am making a distinction between book-smart students and research smart students which in my opinion are not always same).
University brand is a definite thing. I don't know how crucial this would be after PhD. I for sure know that for undergrad, getting a high paying job was directly proportional to the brand of the university he/she graduated from.
Less pressure as people would assume I am not smart (because of mid-level university) and hence I could excel without any performance pressure except for the one which is required to keep the stipend going.

I would like to have some feedback from the current grad student regarding the validity of my reasoning. Feel free to add your own explanation as well.
NOTE: Not so good doesn't mean a bad university, it just means a mid-table university and good university means universities like MIT, Caltech etc.

Just to clarify, you're asking about the difference between them from the perspective of a PhD student?  The answers would be quite different for the perspective of undergrad, postdoc, faculty, etc.

If you are asking from the perspective of a PhD student, then you should replace "university" with "department".  There are strong departments at weak universities, and weak departments at strong universities, and the university's stature/reputation has far less influence after graduation than the department's stature/reputation.

...and as others have pointed out, the same argument implies that you should focus on potential advisors rather than potential departments.

This post is far too broad to be answered, but I can give some anecdotes.
In my experience, there are no "bad" universities provided that you go to a university that has some kind of national standing.  Sure, you can go to the Back Alley University of Cat Medicine and Mathematics, but I don't think that's what you're getting at.  More likely you're talking about whether you should go to a university that has national or international standing (like MIT) compared to one that might have decent regional standing but that isn't a national research powerhouse in your field.
Where you do your grad studies should depend on many things.  The status of the university is perhaps one of those things but is certainly not at the top of the list, especially for PhD.  You should instead be looking at individual researchers.  Do they do the research you are interested in?  Do they regularly publish? Regularly attend conferences?  Then go and meet with them or speak to them via email about mutually relevant research opportunities.  Determine if this is someone who can teach you to become a good researcher in the field.
Your research credibility depends on the problems you solve and the contributions you make.  An excellent school does not make an excellent researcher just by virtue of having them attend the school.
So, what does a top tier university really offer?  First, it tends to attract top tier talent and lots of funding to go along with it. Second, it is highly competitive, so you will be surrounded by other students of presumably high quality.  Third, yes, you get a bit of the brand to go with it.
What does a smaller university really offer?  Assuming you chose your advisor right (hard problem!) then you will probably get the same quality or higher training to become a researcher yourself, compared to going to a big school.  The problems you are working on might not be ground breaking but will always be interesting and relevant - research doesn't care where you study, it cares what you do.
Finally, it depends so strongly on your field which university is the best.  Speaking about my home province of Ontario, Canada, we certainly have some universities that are considered to be top-tier, probably world class, but only in certain fields.  There is a smaller (but still highly regarded) university whose past is rooted in agricultural research and, despite being a smaller university is extremely highly regarded in that field, probably best in the province for it.  However, it is certainly not a world class hub in, say, human computer interaction.  They wouldn't compete with MIT's media lab there, but that's not to say that someone interested in HCI couldn't make a huge impact going there.

+1 for "research doesn't care where you study, it cares what you do." In fact, the "name brand" probably counts more for positions outside of your field -- theoretical mathematicians will evaluate your actual work, whereas if you apply for an R&D job "in industry", they will be ill-suited to judge whether proving Theorem A is more remarkable than Theorem B, and so will rely more on the name brand. From the other direction -- do students at MIT have access to better resources than those at Nebraska? Probably, but also more competition for those resources...

UK perspective
In the UK, the most important factor for a PhD is the supervisor, not the the institution. Unlike undergraduate or master's courses, a PhD does not involve any "classes", so the role of a department is limited to providing a supportive environment for research. The curriculum for PhD study is essentially the same everywhere -- you write a thesis that makes an original contribution to scholarship (of course, there are same practice-based programmes where other types of output may be admissible, but these are usually a different degree title, such as DLitt, DMus, &c.).
Of course, great supervisors are not necessarily distributed equally among institutions -- often, a particular institution may be notable for research in a particular field, causing the best researchers to cluster there. This can vary enormously by field or even sub-field. At the same time, there is no official league table nor a centralised system for allocating academics to institutions, the result being that some of the best supervisors may not be in the obvious places, whether because they are undervalued or because they prefer to work there.
So, to cut a long story short, you should be considering the different between a "good" and "not so good" supervisor.

This would apply equally to the US (and really probably everywhere). Although US PhDs often involve some coursework (roughly joining a UK master's with a UK PhD), nobody cares about the coursework except that the student complete it satisfactorily.

My PhD did involve clases (examined) during the first term, but otherwise I agree with your post.

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Could I ask my supervisor to help me coding an implementation of a scientific paper's algorithm
I am stuck at an implementation of a scientific paper's algorithm, could I ask help from staff to code a part with me or even my advisor to do so?
Thanks for the clarification.

My experience has shown that the answer to this question is no, because it is only your job. So I suggest you do your best.

Get advice from staff or faculty, especially your advisor, but do not expect them to actually do the thing themselves. The goal is for you to figure out how to do it... That is, the implementation itself is not the educational goal for you, but, rather, that you implement the thing. But/and part of your advisor's role would be to help (not quite "do").

what if the thing needs more than just one pair of hands (huge code to implement)

Being stuck is something very much different from lacking sufficient manpower ("needs more than one pair of hands"). Could you please clarify which of these problems you're facing?

Who are the people you refer to as staff? What is your position?

Is your issue more that the paper didn't explain how to implement it (replicability), or that it did but you just don't know how to implement that in code? or both? If there's a replicability issue, did you contact the authors, look at their github, etc.? Have other people confirmed they can replicate the result? Are you trying to replicate a leading-edge SOTA result, or something basic from like 5+ years ago? Not enough specifics in your question. In some fields, there is a lot of gaming in papers, researchers omitting or concealing key details for replication.

I'd like to add to Buffy's answer and some of the comments: It does happen that the difficulty is in the paper rather than the one sitting before it.
I've had a situation where our Master student couldn't figure out how to get an algorithm from a paper working. Neither could I. We decided that they should go on and use a different approach.
I later on met some industry people on a conference who cited the very same paper for one of their products and talked to them about the paper. Turned out, neither had they succeeded with that algorithm...
As Buffy says, yes, do ask your supervisor. They anyways need to know of your difficulties.

Very much yes!  Scientific papers generally have to be compressed to fit into a journal's allowed page length.  The authors thus may leave out a lot of explanation, and indeed, might not be all that good at explaining stuff in the first place.  (I know I'm not :-()  One other thing to do is to check the authors' web sites, since they sometimes have more explanations, or even working examples.

@jamesqf: I omitted the master student's unsuccessful attempts to contact the authors about clarification...

May I ask you which algorithm / paper your student was not able to implement? (out of pure curiosity)

Yes you can ask, but whoever you ask, make sure you check with your advisor first so that you understand the requirements. The answer might be "do it yourself" of course.
But more likely is that, while they leave the task to you, they might point you to some resource that will help you do it. One principle that is important in teaching is to give the students sufficient hints so that they learn how to do things themselves, rather than just giving solutions.
In fact, rather than a direct ask for help, tell the advisor that you are stuck at a certain point and ask for advice about how to get unstuck.
In some fields, it can be appropriate to have others do certain coding tasks. I doubt that they let grad students directly code the Large Hadron Collider at CERN, for example. It isn't a place where you want to hear "oops...".
In general, you can ask for whatever help you need. But not asking and getting outside help could be interpreted by an advisor as misconduct.

+1 to "In fact, rather than a direct ask for help, tell the advisor that you are stuck at a certain point and ask for advice about how to get unstuck." Your supervisor may be unhappy with a blunt statement of "I can't do this"; they are likely to be much happier with "I completed steps A and B; I am stuck on step C; I tried X, Y and Z and consulted resources P, D, and Q, but I haven't been able to make further progress".

I’d add that even just explaining the problem to someone (maybe even a fellow student) will help. Either you’ll become unstuck or you’ll realise your problem is real.

@Pam In the IT vernacular, it's called "rubber duck debugging" (not to be confused with similar-sounding "rubber hose debugging", which is a method used to save time on solving hard problems that others have already solved)

"could be interpreted as misconduct" For a class, perhaps, but for a scientific paper? True, it'd be misconduct if you didn't properly attribute authorship/acknowledgement later (or claimed that the outside help was your own work), but the getting outside help per se as misconduct? Perhaps it's field-dependent, but at least in biomedical, no one expects papers to be the work of a lone genius. -- You may annoy your/their advisor by complicating the author list or taking time from the other person, but those are political issues, not misconduct.

@R.M., I meant, so interpreted by the advisor, which could be enough to sink a student. Edited to clarify.

@Buffy I can assure you large parts of code that keep the accelerators and detectors going at CERN are most certainly written by grad students. The code tends to be not very good(TM),  but that has never stopped physics, though it might have come close a couple of times ;-)

@Marianne013: It seems that although bad code may stop physics research, and may even stop physics researchers who happen to be in the wrong place at the wrong time, it will never stop physics.  In fact for such systems the problem may well be that physics doesn't stop when the code does...

The question is sufficiently vague that I'm not sure why everyone is assuming that your advisor has set you with a goal to implement something from a paper and no one else can touch it because it's a learning experience for you.
Of course you can ask for help from your group - that's why we work in groups. You should definitely ask your advisor who could help you.
In more experimental fields and depending on the scope of the work, your advisor would want to assign a staff member that is paid off the appropriate grant. But generally speaking, assisting someone else with code is a completely normal task that could fall under a staff person's duties if their manager (your mentor) set them to it.

This is an important point. The "assignment" might be meant as a learning exercise, but the supervisor might have believed it's the easiest way to achieve some goal. If it's harder than the PI thought, perhaps other options now have a more favorable cost-benefit profile.

Yes, you should ask for help
Assuming you are more-or-less proficient in coding, it is possible (even likely) that the problem is with the paper itself. In that case you will definitely need your supervisor to help figure this out.
This is part of the reason why I constantly disagree with people saying "post the source" for academic papers. There's no guarantee that what they implemented for their research matches the paper they published. If you implement the algorithm from the paper, you'll catch methodological errors like that.
I've personally had this where my company had paid for the rights to a paper published by a very senior person in the field. His work is repeatedly referenced by a lot of other authors. He should have been top notch.
Instead what we found was that of the 9 papers he'd written on his results, and the 5 separate circuits implementing his algorithm, not one of the circuits corresponded to any of the papers. Not one. When we called him to ask about this, it turns out there was an issue at lower frequencies which the changes in the circuits were intended to resolve.
Except that it turns out these changes invalidate the conclusions of the paper. They added a non-linear element which his algorithm could not deal with. And when we looked at his results, it was absolutely there in the data. He'd only managed to conceal it by quoting his numbers for something like 5% accuracy plus a long-term drift over time, when the field would consider 0.1% accuracy as just about adequate and would not tolerate any control loop drift.
It's possible that he was sloppy and didn't look for this. Or it's possible he raced to publication and thought her could solve the flaws in a later paper. Or it's possible he sold it to us knowing it was crap and simply not caring. If you can't reproduce results, don't discount the possibility that this is what you're dealing with. And if that's the case, you really need to work it out.

Why is that an argument against posting the source?

Though, I personally disagree with your conclusion about posting the source. The reason people post the source is not so that everyone will blindly use the source rather than reimplementing, but rather that when we struggle to reimplement, we can look at the source to see how the authors got the numbers in the paper. Without posting the source, authors can just say "you must have a bug, I don't have time to help you", and it is much harder to prove that the paper is wrong.

As a PhD student, I had this problem - the solution turned out to be to call the paper authors for help.  One group just sent me their code, which was nice. Another clarified some bits I was doing wrong.  I think I remember that one had a typo in the paper, but that might be wishful memory.
However, I would also say I came up in an enviroment where my supervisor definately knew if I was having problems and generaly knew what those problems were because my first action on having a problem was normally to wander into his office and thrash it out on the whiteboard. If you don't have this type of relationship then I suggest you work towards it.

Nice infos to know thanks !


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Is it OK to contact the author of the paper for code review?
I want to make sure that my code is OK and fully compliant with the original paper algorithm, is it OK to contact the professor that created the algorithm for reviewing my code?
Thanks

sure but why would this person spend some valuable time debugging your code?

What is the problem here: (a) the description of the algorithm in the original paper lacks some details (e.g., how normalization is performed), or (b) the algorithm is entirely clear and you just want to be sure you didn't introduce bugs? My answer would differ in the two cases.

both...................

@marcnicole (a) and (b) are incompatible alternatives (algorithm in paper is not clear, algorithm in paper is clear).

What have you done so far yourself to check your code? Have you tried replicating a result from the paper? Have you tested it on other data/input/parameters?

In general, it is ok to ask, but don't expect much except in a couple of special cases. One case is if the professor is one in your own department, in which case they will probably assume some responsibility for your advancement.
Otherwise, you might be more successful if you have something to contribute to them that they would find valuable. If you propose a collaboration on an advance beyond their paper then you might have an opening.
For a student you might be able to have a local professor review the code, rather than the original author. This assumes that the person has an interest in that paper as well, I think.
But a blind ask for a code review is likely to be met with silence.


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Master's thesis, should I inform my supervisor about the mistake?
Please hear me out first,

I am one week away from submitting a manuscript, the deadline is in one week.
The supervisor has reviewed my thesis and is happy with my results.
He is writing a paper based on my work.

Now I used a technique in my work that is fairly different is almost never used, but it yielded good results so I went on. I told my supervisor during earlier days that I using that technique and he said it's not the norm, but whatever you do just document it. He never questioned my decision or said it doesn't work.
Fast forward 13 months, and I've come to know that you are not supposed to use that technique as it introduces some bias in the results, which is not discernable.
Now I am more than willing to inform my supervisor, but this will have a domino effect and I might have to start my experiments again, which will take more than one and a half months at least, and I have been working on my thesis for 18 months now.
Why should I not tell my supervisor:

He has reviewed my thesis and he is happy with my results.
My student visa expires in 21 days, and another thesis extension (if it happens) with the university would be whole another hassle, and I am not sure if I will even get the extension.
No money to pay the rent. this is a big one, up to this point I have survived by a very little margin, with no funding from the department, and I have no work now, another one and a half months would mean at least 70K $ which I cannot arrange.
Visiting parents after 2 years of not going back home because of masters, and short on money.
18 months of already working on a thesis, having done my very best, I am f****ng tired now. I just want to hand in the thesis and sleep in peace. Every single student in my class has given their defense I am the only one left.
I want to move forward with my life, get engaged and find a job. 4 years of master's school, with zero
funding from my department, even when they were happy with my work.
Getting rid of my supervisor for good, he was always pushing me and
pushing me, and I worked my ass for this thesis without any returns.
Not dealing with him would be the highlight of the year for me.
It is a 100+ page thesis, from a different perspective, it shouldn't
nullify all of my work.
I can always plead ignorance in the end. Since I am not from a
computer science background, this thesis is at the CS department
though, they know I am always learning or whatnot.
I can defend it, my supervisor is one of my graders, and he is on my
side.

Why should I tell my supervisor:

It's eating me up from inside. It is my baby, my work, I've put 18
months of work into it. It only deserves to be 100%
My supervisor is writing a paper that he wants to submit to Nature
based on my results, and it has that faulty method I used. This kills
me.
I feel like a fraudster/criminal.
Scared my work will be thesis work might get canceled in the future.

I would be happy if you can help me solve this quandary.

You may just be able to add a note to the conclusion about limitations of the method.

@Dawn, can you expand that to an answer. It would be the core of mine.

Everybody makes mistakes. What separates good researchers from poor ones, is how well we own up to them. I don't know the details of your work, but it is very possible that what you think is a devastating mistake, is an oversight which should simply be improved upon if the work is later submitted as a journal article. Note that it is very rare that a Masters thesis becomes a journal article unaltered.
You should get in touch with your supervisor and tell them that you have discovered this paper, which you think might be warning that your method is questionable under these specific circumstances. Then let your supervisor form their own opinion.


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Is a 2.5 year shorter tenure clock a benefit?
I have a TT offer which includes removing 2.5 years from my tenure clock, the amount of time I have spent in my first postdoc. The papers and grants from the postdoc would be considered by my tenure committee at the new institution.
My teaching and service commitments will go up after tenure, and I have observed and read here about why faculty often are unhappy after gaining tenure.
So , is this really a benefit?

Getting tenure is (technically and in actuality) a promotion and comes with at least one benefit (not easily getting fired) and usually there is a (modest) pay jump. Whether you consider these benefits against the additional responsibilities that tenured faculty have (especially in terms of administrative/service work) is up to you.
A shortened tenure clock could be a good thing as it gets you that promotion sooner. It could also be stressful if you're at a place where the tenure hurdle is clear and you don't think you'll make it (e.g. 7 peer reviewed articles when you have only 2 in the bag and will only get 3 more done by tenure-time)
The best would be to have the option of coming up early -- but also the ability to delay your tenure bid and return to normative time -- but also retaining the ability to count all of your materials from your postdoc period in your tenure bid.  There may be resistance to this, though, as it might be seen as having your cake and eating it too.

"7 peer-reviewed articles": I wish that were the total required. . . .

@aeismail In my experience, this would be a typical requirement for a social sciences person at a lower ranked R1 and a bit high for an R2. OP doesn’t give a subject area.

... Although now I see from the other posts by this user that the subject area is engineering.

Yes, I am in an engineering field. Tenure requirements seen to be readily achievable, given that the papers, et. from my postdoc will be admissable in

I've seen a situation in which someone negotiated for a shorter tenure period and then didn't make it.  It wasn't a nice situation at all.  In general, you're better off taking the entire period or applying for tenure early if/when your committee thinks you're ready.

What field/country are you in? If you're in an area where early-career grants are important, a shorter tenure-clock can limit your access to those.
For the US:
The NSF CAREER grants, have a restriction that you can't submit to the annual summer call if you are due to be tenured before the following October.
Department of Defense Young Investigator grants are a mixed bag, but with less emphasis on tenure status: DARPA allows fall applications into the third year of tenure, Army and Air Force allow applications up to 5 years after PhD (counting post-doc time), and Navy allows applications up to 5 years into your position (with no consideration of where you are in the tenure process).

Engineering, in the USA. I actually already have an early career grant, relieved as a research scientist.


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How to motivate an undergrad class to do research when its not a course requirement?
How can I motivate my undergrad students to do research?
Since these students are at an undergrad level, I don't expect any extraordinary results.  However, I would like if they get something published (even in low impact publications).
Undergrads almost never do research in our country. It's not even a requirement of the course.  But, I want to motivate them for research. If they get something published, it would encourage them in the future.
In our country, research at the undergraduate level is almost non-existent. I want to introduce this concept at the undergrad level, but I don't want to force anything upon them.  I just want to show them the benefits of research.

Well, I don't see why undergraduate students can not do research? In fact, they are young, and they are full of energy and ideas. And research and reading papers are not close-bounded jobs. They are more like skills to be honed over years, like you learn writing from primary school... Its about improving your thinking process, be innovative, be able to ask whys, hows and go beyond whats and which..

I don't think undergraduates should be motivated to do research. They need to come to the realization that they want to become involved in research on their own. Research is not for everyone, and the undergraduates I've interacted with in a research setting come in two flavors: the ones who know why they should pursue research (or at least have some idea of what they are getting themselves into), and the ones who thought it would be something to do to "kill the time," or some such. Which group of students do you think made the experience worthwhile for everyone involved?

I would say, as a teacher, you can allot a project as a mandatory part of course. This project should count towards the final evaluation of the course. You need to do a bit of design and planning about the project and research idea that you want to implement. Then you may divide the work among students based on their strengths and weaknesses. You may assign one group to the whole project and assign individual modules to the students or you may create many groups and each group an individual module. Once this phase of project is over, you will be able to assess the students by their research caliber and motivate the good students for further work, which may be another project with more intensity. In addition to this, you can motivate them to go to better universities and industries for project work. This will really broaden their outlook. They will start looking beyond getting some CGPA and grabbing a job. I hope I could give you some idea :P

This is an excellent idea. In some of my undergraduate courses I have the students do research. How much, how deep, etc. depends on quite a few things but I do think it is a good idea for them to start "getting their feet wet" with the ideas involved.

I think this is the best method, but even so the teacher will need to put in a LOT of effort as far as selecting the research idea and forming it - basically spoon feeding it to the students, doing ALL of the literature survey, checking in as far as progress goes multiple times a week, etc. - even more so for the more junior students.

Have you considered making it some sort of contest?  Students will go to astonishing lengths to win a competition. :-)
I'll give you an example.  One of the undergraduate classes I teach is a C programming class, and towards the end of the term we spend a couple of weeks on performance optimization.  For the corresponding assignments the students are asked to speed up a slow program given to them.  Their score on those assignments depends on the speedup they are able to get, and -- here's the kicker -- if they can beat the performance of my solution they get a 20% bonus.  I've seen students explore exotic data structures and algorithms, figure out how to embed hand-tuned assembly code, and teach themselves how to write multi-threaded code, just so they can say they beat the instructor.  It's really terrific watching them push themselves to excel.
Your situation is almost certainly different from mine, but I think it's still fair to say that students will self-engage, and push themselves to think creatively and explore different solutions, if the motivation to excel is coming from the inside -- which is really what research is all about.

Careful. Competitions appeal to some students, but strongly discourage others, even among the students who are very strong.

I've discovered that an effective way to engage undergrads is to give them a tour of your lab and let them shadow a grad student or other undergrads for a few days. Speak with them as often as you can to gauge what they are interested in and let them get a feel for your research group. Handing students off to a grad student or a postdoc and not speaking to them for a month is not going to work. It would be nice if you can give them a short term goal, say a poster presentation.

One of my favorite undergraduate classes had a original research requirement, as well as a publishing requirement. Neither was very stringent; the original research requirement was that we collect some data on our own, while the publishing requirement was to provide proof of submission of a manuscript. It gave us a taste of research and publishing, which in some caes led to in-depth, sophisticate research while the students were still undergrads.
Don't be afraid to make some research a requirement for your students. They will learn that they are capable of more than they thought, and it is likely that a few students will run with the opportunity and produce results that may surprise even you.

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Never heard back on PhD application but enrolled in MS program
Applied to a private university for admission to an MS program thinking I had no chance being admitted to the PhD program because of my transcript.
Planned on trying to get into the PhD program after the first semester of the masters program. At a welcoming seminar for new grad students a faculty member told me to apply to the PhD program anyway. So I did, back in November for Spring admission. Still have not received a formal decision on the PhD application and it’s the end of the Spring semester. Tried reaching out to faculty multiple times inquiring whether I should reapply etc. have not heard back regarding the PhD application but have on other things like maybe an independent research study over the summer. One of my professors straight up told me sometimes the admission committee purposely does not make a decision on certain applicants because they’re not sure about them yet. Which is fine and understandable in a way. But it’s pretty ridiculous at this point, like I’m enrolled in the MS program, have corresponded with multiple faculty regarding research projects etc. but no decision on my PhD application? What should I do?
I’ve respectfully inquired a couple of times but after sending 1-2 follow up emails I don’t feel comfortable continuing to try because I don’t want to come off as rude but this is very important to my future. The chair even got back to me but only addressed half my email and said nothing of the PhD application. I’m not dumb, I know this could be code for declined, but why not give me a formal response? If anyone wants to know any other details before giving input just ask.

The only question I see can only be answered by someone at that university. Otherwise this seems like a rant.

I sympathize with your situation. To help understand your situation better can you indicate whether it is a US university and if you are an international or domestic applicant? Thanks.  Regardless, please see my response below, which is assuming you are an international student applying to a US private university.
There is a fundamental difference between Ph.D. and MS hires. Most international Ph.D. hires are paid (albeit very little) a stipend and their tuition is covered via research / teaching assistantships. In contrast, MS students bear their own tuition costs and in fact are a source of revenue for university departments. Therefore, money is potentially one reason that is causing this delay from their side.
Another delay is simply due to Ph.D. hiring cycles.  Most professors are part of committees they'd rather not be.  Ph.D. hiring is another such committee.  Therefore, many departments have fixed cycles within which they would proceed with the hiring.  Perhaps, you are ahead of the cycle in your department.  You can check this by asking pointed questions.
Additionally, professors in the US have the power to hire Ph.D.s at will if they have money.  Your discussion with a professor is a good way to ensure that your application is given priority.  However, remember that when a professor hires a Ph.D. student, they begin a long journey (5 years on average) during which a strong working relationship will be established between the two of you. Essentially, they are investing in you.  So keep that in mind in your conversations with the professor.  Furthermore, sometimes talking to current Ph.D. students who are already working in that group is a good way to figure out crucial information about the professor such as "do they have money/funds to support another Ph.D.?  What is their nature and their expectation from the incoming student?  How helpful are they with job searching / student placement later? etc. "
You mentioned an individual research project with a professor.  While it is useful to do this as it indicates to you whether you enjoy research, enjoy working with the professor and lab, it can also be a waste of time if you already know you want to get in the Ph.D. program with that professor.  Regardless, if nothin else works, an individual study is a great way to build a relationship and show your talent.
Lastly, I want to talk a little about approach.  Most students, especially those starting out, will likely be shy of asking the direct (and at times tough) questions.  It is important you mindfully not be shy/apprehensive.  However, also try not to come off as rude/impatient.  Communicating via email is an art that is learned overtime.  However, below are some pointers that may help:

Write short emails with pointed questions
Always try to be pleasant, try to not sound irritated, especially on email
If an email cannot be made short enough to be read in 1 min max., request the professor for an appointment. Indicate that a brief meeting of 15 mins will be enough, and get the conversation going
Use departmental resources such as graduate coordinator staff, other Ph.D. students to get a good idea on relevant background matters

I am pretty sure they are not being non-responsive because they think you are not qualified.  If it were that clear, they would have told you that.  I rather think that there is some kind of miscommunication / misalignment going on.  I hope it is sorted out for you soon.
Best luck!

No I am not international. A professor I was seeking advice from asked me the same thing actually, since that would make this situation more believable in his eyes I guess. I am an American citizen in a US private university that is on the east coast. It isn’t that well known outside of the state it’s in and maybe some surrounding states.

Okay, are you seeking funding for pursuing the Ph.D.?  or do you have a scholarship or something similar that guarantees funding?  You can also apply for doctoral fellowships (potentially in discussion with the professor you'd like to work with), which are often available for US citizens.  The point is that having sponsorship / money makes life a lot easier :) .


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Is it necessary to show what improvements you have made to similar work in literature reviews section?
I have seen quite a few research publications where the literature review section doesn't compare past work to the author's work. It's like:

[1] did this using X technique. [5] used Y technology. (etc.)

This type of literature reviews are easier to write as I don't have to read similar works in extreme detail to create a list of things that we are doing and they are not. I can understand their technique by reading their abstract but it won't matter too much as long as I am using a completely different technology.
I have also seen some good publications which compare each and every work in literature review section to their own work and say "They did not do this", "Their work couldn't do that". While, of course, this looks a lot better but it's a lot harder to write.
Let's say I using queuing theory for a similar work which has been done using some other technique. I can easily state that they used this technique in their work instead of trying to find drawbacks in their work.
So which approach is better when writing the literature review section?

So which approach is better — The one that requires more work.

Contrasting your work with earlier work on the same topic (same or related questions) is a crucial part of a scientific publication. You have to explain to the reader what makes your approach better (or worse) depending on the exact problem to solve.
Now, whether you should do this in the section devoted to review of the existing literature is debatable. There are no strict rules, so as long as you do it somewhere and the paper is clearly readable, just do what seems best to you. If you have trouble writing, I would suggest you separate the content into a simpler form:

State of the art: review of the existing literature. What problems are solved, what are remaining questions, where can we make progress. This is the motivation of your work.
Your methodology
Your results
Discussion of how these results compare to earlier work: you're doing better than A and B on large matrices, but the approach means that you will be slower than C on sparse matrices, that sort of stuff.

How about a write about all the similar works in the literature review section but not compare my work with each of them. At the end of this section I would write "All of these works don't consider as many parameters as my work does.My work uses this technique and covers more scenarios."

@iOsBoy Sounds possible, but be careful to include details about why the extra parameters are useful, what are the scenari and why they are important.

@iOsBoy The idea is to make the reader think "oh, cool, this proposed approach is better because it's faster, or works for a wider domain, or...". But, you have to be specific. Beware of the sentences like the one in your comment: saying "my method is better, easier and covers more scenarios" without giving specifics just sounds like you're trying to "artificially" increase the value of your work, while you don't actually know the advantages of your work yourself. You have to specify the advantages somewhere, and you have to make the reader interested - you can do it together or not.


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How much is an undergraduate student paid during fulltime internship in a research lab in India?
An 3rd year undergraduate computer science student is doing several months full time internship at a research lab in the university. What is an usual budget for such a student per month?

I am an Indian student as well. The only time I have seen undergrad research students being paid is through fellowships/scholarships.
For example, the Indian Academy of Sciences Summer Research Fellowship Program pays research interns of about INR 8000 - 12,500 for 2 months (the last time I checked).
Some institutions hold their own summer research programs every year, which also provide a stipend such as IIT Kanpur's SURGE, which provides a stipend of INR 12,500 for 8 weeks.
Some of the foreign summer internships like Caltech SURF, MITACS Globalink Research Internship, DAAD-WISE pay much better.
But if you are conducting research with a professor directly, i.e. not through a scholarship or a fellowship, it's not common to get paid. This is especially true if you are working as an undergraduate researcher at your own university.
Even in the rare situation that you had the opportunity to get a stipend, it should have been discussed upfront before the internship began.
As shk92 says in his answer, it is considered that the biggest gain for a student is valuable research experience.
So, should you ask your advisor if you can get paid for your internship now?
Here's my suggestion:

How would your professor take it if you made the request? Is it possible he might get angry and think you are being entitled? Will it possibly affect your internship in the future? If you think he is understanding and would consider it, then go through with the next steps. If not, do not bring it up.
Make sure you have made sizable contributions to the project so far.
Ask your professor if you can get a stipend, highlighting the work you have done so far and future contributions you plan to make. Make sure you do not come off as arrogant.
Be prepared for a 'No'.

Thank you! When you say that Caltech SURF, MITACS Globalink Research Internship, DAAD-WISE pay much better, how much it can be? Two-three times more ?

@student: This is a well thought, good written answer. Can you please have a look by yourself? The link has been provided, I repeat it here for your convenience https://www2.daad.de/deutschland/stipendium/datenbank/en/21148-scholarship-database/?detail=50015295

@student yeah the stipend can go to lakhs for 2-3 months. But unfortunately, the application period for them is over for this year and I believe they take in only 3rd year undergrads.

Thank you very much.

Based on my experience in the US, undergraduates working in a university research lab are not paid anything. There are exceptions of course, but they are quite rare.
I'm not sure if "PI" is a common term in India. Just clarifying here that "PI" means Principal Investigator i.e. the person in charge of the lab and its research output and is also the one responsible for obtaining funds for it.
When it comes to undergraduate research, there is a quid pro quo. The PI helps the student gain valuable research experience and the student in turn helps the PI complete a few small projects or helps another graduate student with theirs. And in most cases, the student is the one that benefits the most as they are nowhere close to the level of competence required to complete a project on their own with minimal supervision from the PI.
So to answer your question "What is the budget for such a student?"
Most likely zero. You are paid with research experience. You might think it sucks and is unfair but that is a discussion for another day.
If you want to get paid, you need to go in with a strategy. You can't just go to the PI and say "I am expecting to get paid for my work." You need to have a few key points where you clarify the value you are bringing to their group and that it would benefit them from having you around. If they can let you go instead of paying you and have zero effect on their output, they're going to let you go as soon as you insist on getting paid.

I would note that practices for paying undergrads for research vary widely, even among US institutions. I have no idea what is customary in India, but I would hesitate to make assumptions based only on my experiences in the US.

Thank you for the answer!