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In my actual research work, I need some functionality that is not supported natively by any existing solid tools. So I have two choices: rather I implement this functionality my self, or I use an emerging tool which is in beta version. So, can this have a negative impact on the acceptance of my results by the research community? (I mean when I publish it in a scientific paper)

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At the end of the day, the main requirement is that you can trust the tools you're using. If you're using open-source software, then you may want to double-check that the algorithms are written correctly. If you're using proprietary software, then you may want to consider verifying results with other software for at least some samples.

Note that this is true with any open-source package. For my thesis work, I used a particular open-source analysis toolkit which was very popular in the community. They were regularly releasing updates as people investigated the software and found small glitches. During my regular use, I even helped uncover and report a moderately serious bug that would have resulted in bad output — and possibly erroneous conclusions — in a particular edge case. Always know the limits of your tools.

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There's no simple rule about what sort of software is acceptable. What you do needs to be reliable, publicly documentable, and justifiable. Some beta software satisfies this, and some does not. Ultimately, you need to be able to make the case that your methodology (including the software you use) is trustworthy. Even assuming it is, you need to be able to convince other researchers. If you aren't sure, then you should consult with experts about the particular software. If you're a grad student, then asking your advisor would make sense.

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Precisely: the tool doesn't matter as much as the end product that you use it for. You have to make a case for the end result, and if that hinges on the validity of the tool, then you need to justify the tool. Its status is irrelevant. – Suresh Jan 31 '13 at 16:57

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