Ask Slashdot: Successful Software From Academia? 314
An anonymous reader writes "A lot of masters and PhD theses are about development of software targeting the solution or the automation of a specific problem. Bioinformatics, for example, has a lot of journals about software tools that are coded in academic environments; some of this software is the final result of a four-year PhD. But my question is, how much of this software will see the light outside the universities? I know of some examples, like BSD, but they are an exception, right? Is there any list of successful software created entirely inside universities' labs that became widely used?"
Under sufficiently large definitions of "widely" (Score:2)
http://www.cs.wisc.edu/condor/ [wisc.edu]
http://www.redhat.com/mrg/grid/condor/ [redhat.com]
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WebCT was developed at the University of British Columbia, became widely used enough to become a company and then it was big enough to be bought (and put out to pasture to die) by Blackboard...
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You really need to define what you mean by "created" and "entirely within." Very few software development projects are purely academic and a lot of development is done with both academic and non-academic contributors.
Re:Under sufficiently large definitions of "widely (Score:4, Interesting)
Isn't the first one that comes to mind the world wide web? CERN is definitely academia. I'd imagine many other protocols originate in academia. Any idea about SMTP, Usenet, etc.?
BSD, X11, Mach, PostgreSQL, and SSH were all explicitly academic projects.
There is also a question about what qualifies as academia beyond simply universities and government labs. Linus Torvalds started Linux while a PhD student but later landed in industry. Bjarne Stroustrup worked at AT&T Research when he started C++ but he landed at Texas A&M shortly after.
Virtually all programming languages originate in or near academia : Lisp was MIT. Python was started at CWI. Haskell. OCaml. etc. Among the non-academic languages most originate within huge organizations who's research departments start to resemble academia : Smalltalk was PARC. Fortran and Cobal were IBM. C was AT&T. Erlang was Sony. etc. Java and Perl were seemingly further from academia, but academia's influences upon them abound.
Afaik, all computational libraries used for serious numerical programming, like stock trading, computational fluid dynamics, etc., were developed in academia.
Defining success as outside of the university...? (Score:3)
That seems silly. When I worked in a bioinformatics group as an undergrad, we use a *LOT* of software that was only used inside of a university, partially because the kind of research it targeted wasn't necessarily popular in commercial areas yet, and some because what we used was OSS and many commercial organizations preferred closed sourced alternatives (sometimes for speed optimizations, sometimes for support reasons).
Maybe you should define your criteria as widespread use in the context of the target field, rather than outside of a university?
That being said, I think a lot of it either directly or indirectly (through a third party reimplementation), does make it out.
Written for advisor(s)/committee (Score:2)
PostgreSQL? (Score:4, Informative)
PostgreSQL [wikipedia.org]
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Beat me to the punch there...
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A lot of database systems start out as academic research systems that are later commercialized. Examples include H-Store (commercialized as VoltDB), C-Store (commercialized as Vertica), Monet (commercialized many times, the latest incarnation is VectorWise).
Actually, the entire database field traces its roots to academic systems, starting with INGRES which was published in the 1970s by UC Berkeley.
kerberos (Score:2, Interesting)
kerberos, ganglia, folding?
"Widely used" isn't the norm (Score:4, Insightful)
In this day and age, most good software developed in acadamia tends to get spun into a business venture that makes its academic developers very, very rich. See Google, for example.
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In this day and age, most good software developed in acadamia tends to get spun into a business venture that makes its academic developers very, very rich. See Google, for example.
And Sun, and SGI, and Oracle, 3Com, that list is almost endless. There are many commercial software packages for fluid dynamics, molecular dynamics, quantum mechanics and a host of other engineering and scientific fields. MathCAD and Mathematica are some examples along with PATRAN and NASTRAN, CHARMM, VASP, etc. There are TONS of companies that are software spinoffs from universities. TONS of them die every year, too, and end up sold off to patent trolls if they are lucky, err, cursed?
Possible example: (Score:2)
Well, (Score:2)
Logical Reason for the Dearth (Score:5, Insightful)
When software is widely adopted, it is because it has been widely supported and is a more generalized solution to a problem. If it uses hardware, it supports all kinds. If it reads or writes files, it covers all formats. This leads to widespread adoption but also takes a lot of time and a lot of contributions. If you're also working on your thesis, this is a daunting task to work on the side.
Nobody gets their PhD by making a predecessor's implementation support more file formats or hardware. So this is left to the licensing of the originator and the community -- who are often recognized as the real workhorses that go from prototype to actual usable software. That's why you don't find many PhD projects turned instant open source hit.
In bioinformatics , a relatively young field, most consumers of the software work in a lab and the input is fairly simple. But even with simple input they first had to agree [wikipedia.org] on a format [wikipedia.org] (those are just a few of what used to be many). BLAST [wikipedia.org] and FASTA [wikipedia.org] go back to the 1990s and 1980s respectively
Re:Logical Reason for the Dearth (Score:4, Insightful)
The problem with software in academia is that it is often devoted to a sole purpose. It is not a generalized solution -- conversely -- it's often a demonstration of a solution so specific that it's never been done.
Absolutely true. And much of the software is nearly unusable by anyone else-- it was built by the researchers to validate their own work, not to be used by others. If you've ever tried to use any code generated by grad students, it is often buggy, brittle, inflexible, indecipherable, etc... (I'm a late-stage PhD student, so I've run into this MANY times...) And that's the code that the researchers saw fit to release to the public-- imagine what the stuff that wasn't released looks like.
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I used some stuff in my thesis that was written in Fortran 66, adapted from Fortran IV of all places. It took years more to clean out the rest of that and get everything at least into F950/95. It's still buggy, brittle, inflexible and probably indecipherable, but it's slowly getting better and more adaptable.
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Actually I probably should have mentioned that I think it's a further reason for the problems - the code is often patched together from inherited libraries and routines passed on by the PhD supervisor, who themselves inherited quite a lot of it from their own supervisor. Some code used in large academic projects honestly dates back to about 1970 or before, and hasn't been touched since other than to hack into double precision and hope that that doesn't break something subtle. Since some of these archaic rou
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I used some stuff in my thesis that was written in Fortran 66, adapted from Fortran IV of all places. It took years more to clean out the rest of that and get everything at least into F950/95. It's still buggy, brittle, inflexible and probably indecipherable, but it's slowly getting better and more adaptable.
Bah! I've tried to read code that was auto-translated from fortran to c. (Also, I was walking uphill to work both ways! :)
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Haha, I'm in cosmology - one of the "big" CMB codes is CMBEasy, which for almost a decade was the only CMB code written in C++. The author originally "wrote" it by taking an F77 code (CMBFast), about half of which is inlined for speed and which is replete with common blocks with variables arbitrarily renamed for reuse in different routines (the original variable name obviously *also* being used in the routine) and running it through f2c, and then goggling at the result and trying to make sense of it while h
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The problem with software in academia is that it is often devoted to a sole purpose. It is not a generalized solution -- conversely -- it's often a demonstration of a solution so specific that it's never been done.
... it was built by the researchers to validate their own work, not to be used by others.
The main purpose of academic software is to produce papers ... except for text mining software, which does the opposite :)
Software engineers would be horrified at most academic software, which tend to have just one 'release'/version, no source control, no formal testing framework, no design documents, no possibility of bug reports, etc. I know because I used to write stuff like that...
Nowadays, I contribute to projects that have these things (CDK, bioclipse, my stuff on github) but I've seen some bad exampl
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You hit the nail on the head.
However they tend to suck in different ways.
Open Source: We did the fun coding portions and we got it to work. But we will leave out making a clean UI. It is open source someone may come in and do it at some point... Oh by the way we will not bring in any of your UI changes into our project because we got use to using the program the way it is.
Closed Source: It works... It looks good... Lets hope you never see how we got it there... And we will never touch that function again,
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In bioinformatics , a relatively young field, most consumers of the software work in a lab and the input is fairly simple. An open source effort could pick up that slack but then who deserves credit for that work?
Well one good example of generally used academic software is RasMol, and it's (spiritual) successor, Jmol. RasMol started as a project by Roger Sayle as part of a PhD on graphics software, but became the main free viewer for macromolecular structures.
Jmol has taken the idea of a viewer much, much further and is even used by mathematicians to show surfaces. It now supports translucent surfaces for orbitals, a complex scripting language like a subset of javascript, and reads a large number of file formats. It
Tons (Score:2)
I don't know of any list but I'm pretty sure that tons of successful software has come from academia.
Racket [racket-lang.org] is a particularly nice example. I'm too lazy to Google so perhaps others can provide a few hundred more.
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X Windows, Ingress / Postgress (Score:3)
Subject says it, X was mainly developed at MIT. I guess Ingress and Postgress where originally also university projects.
A few... (Score:5, Informative)
* Kerberos (Widely used, part of Active Directory)
* X11
* AFS (Andrew File System)
* MACH (Used by GNU HURD and OS X)
And that's just a starting sample.
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A couple of more recent examples, now in wide use:
* LLVM (University of Illinois)
* Xen hypervisor (University of Cambridge)
In general, if a University project becomes widely used it will either have been spun off into a commercial operation or become an open source project which gains outside contributors.
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rsync
Web Browsers? TCP/IP? (Score:2)
TCP/IP [wikipedia.org]
I'm pretty sure these are used outside of universities.
Several (Score:3, Informative)
Windows? (Score:2, Funny)
Oh wait that was Pre-K
Yes (Score:2)
There are quite a few open source projects on bioinformatics.org [bioinformatics.org]. Some of these are little more than quick command line tools. Others are entire frameworks. Personally, I use the following tools on a regular basis. Bioconductor (with R), EMBOSS, Primer3, and ImageJ.
TeX (Score:3, Insightful)
Subject of several theses:
http://www.tug.org/docs/liang/ [tug.org]
http://www.pragma-ade.com/pdftex/thesis.pdf [pragma-ade.com]
https://www.tug.org/docs/plass/plass-thesis.pdf [tug.org]
(John Hobby's on METAPOST http://ect.bell-labs.com/who/hobby/thesis.pdf [bell-labs.com] )
Probably others. More information at
http://www.tug.org/ [tug.org]
and
http://www.latex-project.org/ [latex-project.org]
and
http://wiki.contextgarden.net/Main_Page [contextgarden.net]
William
Wrong approach? (Score:2)
I think this is the wrong question to ask/wrong approach to take. Providing a final, production-ready product is not usually the goal of scientific research (my area). Especially when it's not done in collaboration with some engineering firm.
Usually the goal of scientific research is to provide new knowledge about some very specific domain. For example, some of my coworkers are developing a "cloud simulator" which models EC2 and allows you - among other things - to do stuff like predicting how many machines
Advanced Aircraft Analysis (Score:4, Interesting)
It started out as someone's graduate research project in the late 80s/early 90s, and today it is the #1 aircraft design software tool in the world. Its installed in universities, aircraft manufacturers, aerospace consulting firms, and government and military institutions across the planet.
Disclaimer: I worked on the software after it went commercial.
Few off the top of my head (Score:2)
Silly question (Score:2)
Everything from GNU and Symbolics to (as others have noted) PostgreSQL, Google and beyond.
Let's not forget programming languages like Python and Haskell. Even Facebook was conceived in a university environment, if not as a part of any specific research.
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Even Facebook was conceived in a university environment, if not as a part of any specific research.
Careful now, fella. You are coming darn close to saying something nice about Bill Gates. This *is* Slashdot, ya know.
LLVM (Score:5, Informative)
The backend for quite a few compilers, and a few shader compilers...
Students are short term (Score:3)
Is there any list of successful software created entirely inside universities' labs that became widely used?
That is an odd restriction to make. Students are only at university for a short time. If their work during that time turns into something useful then they naturally continue it after they leave, either as a an open source project or as a business venture. This is how it is meant to work, and there are tons of examples of such software.
MATLAB and Maple were both created at universities and later commercialized. Same for SPICE. On the open source side there is Apache, Sendmail, PostgreSQL, and the original implementations of nearly every RFC protocol on the internet.
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Squid...don't forget that one...or Macsyma... :-D
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+1 for Maple that really changed the world (of both mathematicians and engineers) and set the standard of formal maths years and years before its pale private copy Mathematica...
Mosiac (Score:4, Insightful)
Answered in the post (Score:2)
Posted by timothy on Tuesday September 27, @10:41AM from the how-about-ncsa-mosaic dept. [wikipedia.org]
autostitch (Score:2)
I think autostitch is used in real life....
http://www.cs.bath.ac.uk/brown/autostitch/autostitch.html [bath.ac.uk]
LINPACK/LAPACK/Netlib (Score:3)
there's a whole host of Linear Algebra-related software written for high performance computing environments that is attributable largely to various teams of academics throughout the past 30 or so years. It is my understanding that these libraries get used by most anyone doing high-performance computing.
http://www.netlib.org/lapack/ [netlib.org] http://en.wikipedia.org/wiki/LAPACK [wikipedia.org]
FFTW (Score:2)
Here's a list of my (important) favorites:
meep (finite difference time domain electromagnetics)
FFTW (fourier transform)
MPB (photonic bandgap solver
Elmer (finite element solver)
Depends on who you ask... (Score:4, Interesting)
Frequently the software doesn't start in a given academic lab, so much as it starts somewhere in a given research community and propagates to the academic labs as research needs dictate. ImageJ, for example, started at NIH, but now it's available to all and in use all over the place (including my lab).
Other software is developed cooperatively, and then academic contributions are added as they're needed to enable someone's research. If you run R (the statistical program) and start looking through all the extensions available in CRAN, you'll see tons of additions that have been generated in academic labs and released for use by the wider research community.
I work in biomechanics, and I've seen a few programs come out in that field through largely academic development. AnimatLab began (I think) at Georgia Tech, and I think Cofer et al. are still developing it within the university. OpenSim started at Stanford as an open source musculoskeletal simulation program, and is vastly preferable to the godawfully expensive SIMM, which does pretty much the same kinds of things. OpenSim is still alive and well at Stanford, although the developer network spans multiple institutions, academic and otherwise.
Much as I might wish that I could spend more of my time developing programs and playing with software within the academic sandbox, more often it's simply more practical to cast the nets for software from someone, somewhere doing somehow similar research, and then using the software you find if it's useful to your work, rather than reinventing the wheel in favor of advancing academic software development.
rsync (Score:3)
IIRC, rsync was the culmination of its original author's thesis.
HPC Applications (Score:2)
A number of HPC applications funded by NSF/DARPA/DOE grants are able to provide a continued source of new research while maintaining and improving the applications.
One example is OpenMPI. BLAS/LINPACK/LAPACK are also examples. Some of the C++/Boost libraries also are maintained in academic, such as the Boost Graph Library.
-Chris
Ho ho ho (Score:4, Informative)
FWIW, I'm a PhD student at a reasonably large institution in the US.
Very little of this stuff sees the light of day. The vast majority of software is written simply as a proof of concept for some particular method/system/algorithm in order to get published. Good conferences/journals will typically want not only a well thought out idea, but an idea that you can and have implemented it to some extent, and that it works. That having been said, most of what gets produced is complete and total garbage -- typically just enough code to be able to prove that something runs correctly and in a given amount of time.
Personally, I have written a bunch of junk code during my time here. I'd like to think I know more or less how to write good code after all these years, but writing good, well documented, well tested code takes time we don't have -- writing code is simply a means to an end (publication) -- and so most of the code I write is hasty and ugly. This even applies to code that people say is for "wide distribution".
Before you go hounding on academia however, I'd warn that writing "good code" isn't really the point of what we're doing -- the point is to produce a reasonable method of solving some particular problem or type of problem. Going into bioinformatics for example, there are a whole bunch of problems that involve performing more efficient analysis of certain types of graphs. If a researcher discovers something along these lines, he/she will likely write some junk code to prove that the bare algorithm works, perform some analysis of it, publish it and move on. This may or may not end up actually being a useful improvement -- if it is however, then some implementer whose actual job it is to code whatever medical software might be using this algorithm then has a basic blueprint of how to proceed.
As for some examples of software from academia that have made it out, let me think...
Coverity - static code analysis tool, started at Stanford then moved into being a startup and is now quite successful
PostgreSQL - Originally from Berkeley
Bro (Intrusion Detection System) -- written by a researcher from Berkeley/ICSI -- is still somewhat "in academia", but I have heard of several production deployments
That's all I feel like coming up with right now, but I think the general pattern here is that if/when some piece of software produced in academia is seen to have value in its own right (e.g., away from the original research/publication that spawned it), it typically gets spun off in a start-up or a more concerted effort is given to its development, at which point one can actually spend the time to write good code.
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Thank you for posting this. It explains why so many of the Academic solutions to problems I'm researching are so incredibly lacking. I've seen 200+ page theses claiming to solve a problem, but after getting through them I find that the paper actually only describes how one would go about solving the problem and the author hasn't produced one shred of real code, but lots of pseudocode, to make their point.
Honestly, this is why managers avoid hiring Ph.D.s like the black plague in the software development wor
Wuala (Score:2)
Loaded question (Score:2)
This is a loaded question:
But my question is, how much of this software will see the light outside the universities?
The truth is that most software projects (even the ones developed outside of Universities) never get widely adopted. Just take a look at Sourceforge, how many of those projects become widely adopted? or even get anywhere? 1 percent? 0.00001 percent?
That being said, I believe Universities have a disproportionately strong influence on the software industry (which is by design of course). Take for instance, Intel, Linux, Google, InfoSeek, SendMail, Internet Explorer/Netscape (which bo
Definitions of success. (Score:2)
Does a software package need to be "widely used" to be classed as "successful"?
My company, for example, was built around an academic software package. We are nowhere near the league of the Googles or Oracles out there, but we provide a fair number of employees with a good salary. I'd never say our software was widely used as I can count our customer base on the digits of my hands and feet. Our kind of niche market will often use software from academia - because that's the main source of innovation - and
Most projects spin off (Score:2)
If you're looking for examples of "successful software created entirely inside universities' labs", you're never going to find anything. University research is fundamentally different from product development. While a grad student or faculty member might do research on a hard problem and write some software to solve it and publish a paper, that software is going to be enormously buggy, perpetually incomplete, and probably require constant support in order to work at all.
But there's another side to it, whi
In my experiance mostly no (Score:2)
While there are some academic software projects that make it big, that vast majority don't. This is because PhD's are trying to do research, publish, and get their doctorate, not write quality code. I know I would never release any of the code I have written so far, not because I'm anti-FOSS, but because the code is crap and I know it.
The software is written to see if something was possible, or to scratch some very specific itch. The result is that there is no documentation, very little abstraction, and a
listing successes (Score:2)
Etc.
Impossible to answer. What defines a serious project versus someone's pet project or proof of concept? Then of those, how do you measure success? How many Sourceforge projects "see the light" outside Sourceforge?
This is the question you seem to be getting an answer to i
spice (Score:3)
Spice bred a large family tree (Score:2)
There were two very different versions of SPICE - SPICE2 was a fortran program, and is the basis for the PC version PSPICE (Microsim>OrCAD>Cadence) and minicomputer version HSPICE, though many newer simulators are based on the code for spice3 re-written by a subsequent Berkeley effort in c. Its legacy in electronics engineering is such that even independently generated simulators (Eldo, spectre) rely on the conventions and methods from SPICE, though incorporating incremental improvements (a new algori
Universities aren't/didn't-used-to-be Corporations (Score:2)
SAS and R (Score:3)
BIND DNS (Score:5, Informative)
BIND [wikipedia.org]
BIND was written by Douglas Terry, Mark Painter, David Riggle and Songnian Zhou in the early 1980s at the University of California, Berkeley as a result of a DARPA grant. Versions of BIND through 4.8.3 were maintained by the Computer Systems Research Group (CSRG) at UC Berkeley.
SAS (Score:2)
Multi-Touch (Score:2)
In relation to another post - Multi-Touch as implemented in the iPhone came from Academia ....
Porrf of concept (Score:2)
I think the original poster is looking at it from the wrong perspective. Often academic research papers are about a new technique and any accompanying software is rather rough from a user standpoint. Such software in not intended to be marketed to the masses but rather to demonstrate that the idea is sound. Business then takes ( licenses ) these ideas, improves on them and produces something that they can sell. Just because academia doesn't directly market software doesn't mean that their contribution t
One or Two (Score:2)
the University at Champaign-Urbana lays claim to one or two projects that have some popularity ..
the Mosaic browser and its offshoots Netscape, Internet Explorer and Oracle Screens began there.
Javascript (as part of Netscape??)
Apache web server
Project Gutenburg
and, if 'travelling' across the universe fictionally counts as 'widely used outside of the university' then there is HAL in 2001, that (who?) claims to have been activated at the Urbana campus.
WordPerfect (Score:2)
The original version of WordPerfect was developed by Bruce Bastian while a grad student at BYU (with Alan Ashton as his faculty advisor). At that time, it was a screen-oriented editor that ran on Data General minicomputers. I know because I shared an office with Bruce during my senior year at BYU (1977-78) and used his existing version of the editor to write several papers for my classes. :-) Bruce & Alan went on to sell a (DG) version to a local city government (Orem, UT) and then founded Satellite Sys
GIMP (Score:2)
Gimp... Well at least the core image processing part was an 11th hour switch from a failed LISP compiler thesis project.
AMANDA (Score:2)
Written at University of Maryland College Park.
Solves the problem of backing up zillions of servers and workstation to a single massive storage medium (tape, SAN, whatever)
http://www.amanda.org
Lua (programming) (Score:2)
It seems no one has mentioned it yet, so I will.
I believe Lua (the programming language and virtual machine) is from academia -- the Pontifical Catholic University of Rio de Janeiro in Brazil.
Lua is used in a lot of games and embedded in a lot of software. I think even World of Warcraft makes use of it.
For more information and links, see About Lua [lua.org].
Emacs for Windows (Score:2)
NT Emacs (now GNU Emacs for Windows) [gnu.org] - University of Washington Computer Science and Engineering
OCaml (Score:2)
Add R to the list (Score:2)
However, some of the modules which people find really useful are rewritten by the core team, so one could say that they were not an output of the PhD/Masters.
In the larger scheme of things, the solutions by academics remain solutions for academic only until they are widely adopted. Then they permeated textbooks, and become the standard solutions of a useful problem. For this, there will exist a soft
That's a bit flamebait-y (Score:2)
That, and very few people complete a bioinformatics PhD in 4 years as asserted in the summary - unless they enter the PhD program with a master's degree already in hand - most take more like 6-7 years. It can often be one of the most difficult PhDs at any institution in part to
SAGE (Score:2)
The math tool. [sagemath.org] Fantastic piece of software.
Tripwire (Score:2)
Bioinformatics (Score:4, Interesting)
The 'problem' with bioinformatics is that the field is extremely broad. Unless you write BLAST or one of the big sequence assemblers, your software is only going to appeal to a tiny fragment of an already small bioinformatics community.
I wrote software as part of my Ph.D. that is now distributed world wide. I guarantee you've never heard of it - it sets the standard for how to do certain types of phylogenetic analysis, but almost no one does that analysis.
During my time as a postdoc, I wrote a very simple curve fitting routine and put a minimal GUI on top of it. I am now getting requests from multiple countries to modify it to read in files from their instrumentation. Once again, only the tiniest handful of people care, but for those people, this is revolutionary stuff.
The question here is, how do you define success? Like a lot of the responses to this thread, I wrote a small script here or there to solve my own problem. Turns out, it solved a problem for someone else, too. My best known piece of software was a hack, a one-off script, written in an afternoon, that I got yelled at for even bothering to spend time on, and was only ever intended for my own use. It turned out to be the lynchpin for our project, got published in a peer reviewed journal, and has since gone global. I found out later that one of my undergrad computer science profs had solved the same problem 20 years before I did, in a more elegant way, and published it in a good, but non-science, journal - no one has ever heard of it.
Neither of us had the expectation that our software would amount to much. I would define the prof's work as 'successful' - he published a paper on an interesting academic topic. I would define my software as 'wildly successful' - I got an unexpected publication and a global (if small) user base, along with a reputation for fixing problems that would later get me a good postdoc position.
This isn't really an academia question. The most common advice in the open source community is 'scratch an itch'. Write something to fix a problem you see. If you write good stuff, maybe your code will become 'successful'. Or, maybe your afternoon worth of hacking will just turn into an afternoon worth of experience you can apply to the next problem.
A few (or perhaps, more than a few) (Score:4, Informative)
archie -- Princeton?
CAP (appletalk for Unix) -- Columbia
cops/tripwire -- Purdue
GNU everything -- MIT
Gopher -- Minnesota
Kerberos -- MIT
Khoros -- New Mexico
Mach -- CMU
NNTP -- UC San Diego
Mosaic -- Illinois
sendmail -- UC Berkeley
BSD -- UC Berkeley
RCS -- Purdue
Usenet -- Duke/UNC
tcl/tk -- UC Berkeley
multi-CPU Unix -- Purdue
cu-seeme -- Cornell
I'm sure I'm forgetting quite a few. And of course not all of these are STILL successful, but in their day they made their mark, and often paved the way for other projects.
Re: (Score:2)
Blackboard.
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Backrub (Google)
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Blackboard.
*shudders*
Someone tell me their thesis was rejected...
moodle (Score:3, Interesting)
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Re:How about... (Score:4, Informative)
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And Mach (kernel developed at CMU, used in NeXT and MacOS).
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Universities also can't fund large scale testing, and, generally, the university doesn't own the work, the author does (professor or grad student), as soon as something can make money you leave the university, or at least farm it out to a separate corporation.
MSc's and PhD's aren't really about writing a big full blown program though. They're about finding novel solutions to problems and demonstrating that with a program. So they're different goals. You may have a big enough team that you produce a full
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If it doesn't *BSD definitely does.
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Linux itself wasn't used for a thesis or for grade was it?
Parts of the kernel might have started that way, but as a whole, wasn't it just a project for self-education, fun, and production of a more useful too than what was otherwise available?
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It started out that way - but by the time Linus graduated in 1997, linux had become a huge thing, and I bet that if he hadn't made it the topic of his masters - he wouldn't have finished at all.
It started out as a method for Linus to access his work on the school Minix computers (source: Just for Fun [amazon.com]). He later did use it as part of a Masters project for doing multi-architecture Operating systems, but that's it. It is mostly a development as a personal (prior to 1995, part-time/full-time without pay while he pursued academic degrees) and commercial (since 1995 when he's been paid to work full-time on it) project.
Re:Linux (Score:4, Interesting)
The title of Linus' thesis is: "Linux: a Portable Operating System" - so yes, it counts.
The real question is, if it is enough that a project can trace it's roots back to a academia - even if >90% was added later and or by developers outside academia. I bet many products considered purely commercial started out started out in the back of the head of students during their studies. Many of those dropped out to build a company rather than stay and write a thesis about it. If you include those, and even consider some studying other majors than CS - your probably looking at the bulk of all software in existence.
Yes & no (Score:4, Informative)
As I note upthread, virtually all important programming languages originated in academic-like environments, even if they are officially corporate.
There are I think two revolutionary non-academic programming languages :
- Smalltalk was developed by Xerox PARC, but ultimately created object oriented programming, which certainly used academia to gain traction.
- C was developed by AT&T, but completely revolutionized our world. It's almost surely the most important language ever written. There had been structured languages before. I think Fortran and Cobal were developed by IBM. And academia had all it's research and teaching languages. Yet, it was C that brought structured programming and type-safty to system level programming, previously dominated by assembler. Imho, const is pure genius. C could not help but succeed with or without academia, but AT&T was still a fairly academic environment at that time.
In other words, your classification of generalized academic project doesn't include either afaik, but clearly both can fall under some generalized academia. You could not design C, and maybe Smalltalk too, without thinking deeply about languages from a hybrid academic and industrial perspective. If you pursue a blind industry perspective, you create garbage like PHP or VB.
Re: (Score:2)
Re: (Score:2)
Apache got its start when NCSA (U of Illinois) decided to turn support of their httpd server over to an outside group.
Rumor has it that, upon looking at NCSA's code, they remarked, "This certainly is a patchy web server" (true?).
Re: (Score:2)
Hspice and Pspice are popular commercial, closed source versions of Spice. I wonder if Spice would be used more or less if it had been GPL? It certainly resulted in a lot of money that did not go to the original developers.
Re: (Score:2)
You are getting R confused with S. S is a language created at Bell Labs. R is a FOSS implementation, written in the academy. R is the mozilla of stats software where, "there is an add-in for that." An approach that has not worked/happened for other stats software which focus on the cathedral model.