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What were the design decisions that led to R having often more than one way of doing things, that have subtle difference? See, for a good example,
https://www.r-bloggers.com/r-na-vs-null/
More more such issues are here, some which are justified, some which are not http://r4stats.com/articles/why-r-is-hard-to-learn/
From a software engineering perspective, having such choices in a language screams for having subtle and hard-to-find bugs in your code (e.g. in Python the whole point of writing "pythonic" code, that avoids ambiguity and is easy to read and consistent in style). So there must be some major advantages of having that. What are they?
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When should one consider using a metamodel in place of an expensive analysis component? I haven't actually seen an example of an openMDAO project that uses metamodels yet, so I was wondering if they're recommended or whether it's still best to treat expensive analyses like normal ones.
Using a metamodel is a trade-off. You trade accuracy vs execution time so it is up to you in your context.
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I have looked around and have not found many opinions on if it is important to update your R software as soon as a new version is released.
Any opinions would be welcomed!
As with any software, you should carefully evaluate what is included in any new release. If the release consists only of bug-fixes, it is usually expedient to install it as soon as it is practicable for you to do so. If the scope of the release is more expansive -- new features, etc. -- you should review the release more carefully.
If you're in the middle of an important project with a killer deadline, it's quite reasonable to wait a little while before applying any update.
Also, you should as a matter of routine re-run a selection of jobs, that you know the answers to, in order to be sure that the answers are still the same. "No, mistakes of this nature don't happen often, but they do happen."
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i have been given to design software.i have designed the overall process using box and arrow notation .i want to know for high level design of software is there any specific notation to follow.
One of the most commonly used notations is UML or Unified Modelling Language.
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I came across this video of Uncle Bob speaking about the SICP book and the assignment statement and it made me think (and read the corresponding chapter from SICP).
I'm wondering whether the arguments listed (local state, side effects, etc.), considering the first edition was published in 1984, are still a problem in modern languages like Java and C#. It may have been a problem then. Is it still now? Or has something changed?
For example in Java we have immutable Strings. A particular area I can think of where assignment is detrimental is concurrency (correct me if I'm wrong). No assignment means no synchronization and no resource deadlocks, right?
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Can anybody tell me about 'profiling' in unix by giving a small example.
Thank you!
You'll need to give us some more context if you want a useful answer. Broadly speaking, profiling a program is to instrument the executable with some extra statements that record details of execution which you can later analyse to identify parts that are slow, consume too much memory, consume too much CPU etc. Here's a quickie along with examples on how to use gprof which is the GNU profiler for C. http://www.cs.utah.edu/dept/old/texinfo/as/gprof.html#SEC2
If you want to shine in your exam about profiling, talk about Dtrace.