I take it by "strict typing" you mean static typing? What's so great about it? Lots of server-side languages and frameworks (Python/Django, for example) are dynamically typed. I guess I'm not gettting what your point is here.
Strict/weak and static/dynamic are separate and orthogonal properties of languages.
Static typing means types are determined at compile time, as in C/C++, Java, Haskell, etc. Dynamic typing defers type checking to run time, as in Perl, Python, Erlang, etc.
Strict typing means that the type system cannot be "bent" by things like casts and unions in C, or by behind-the-scenes type conversions in Perl.
C is statically and weakly typed. Perl is dynamically and weakly typed. Python is dynamically and (fairly) strongly typed. Haskell is statically and strongly typed.
There seems to be a confusion in many posts between pure and applied mathematics. Applied mathematics is used to describe the physical world, and thus successful mathematical descriptions are discoveries. But mathematics is also used to describe mathematics. This is pure maths.
In pure maths, you can invent mathematical objects, and define their properties and relationships in a logical sense. These definitions are axioms. Then you can discover facts about this invented world. These facts are theorems. This has already been said more briefly in previous posts.
Disclaimer: I am an applied mathematician, but I appreciate the value of pure mathematical theorems related to the maths I use.
... how about giving us the option to directly open MIDI files?
Rosegarden http://www.rosegardenmusic.com/ is an open source music notation editor and MIDI sequencer that can open a MIDI file, and attempts to convert it into music notation. It only runs on Linux, as far as I know. The conversion is rarely accurate in respect to the original score the MIDI was based on, as Rosegarden has to guess things like bar (measure) placement and tempo.
Mathematical skills tend to depend on earlier learned skills. If you do not understand basic algebra, calculus will be nonsense to you, because the (rather difficult) ideas of calculus are usually presented in algebraic form. If you do not understand calculus, you will not understand Fourier transforms. I am sure many people fail in mathematical understanding because of missing links. Lacking these, all further mathematics that depends on these links is incomprehensible.
Contrast this with historical knowledge, or let us say general knowledge. The facts of history tend to be atomic, and the purely theoretical links between these facts are not very important, given that theories of history are probably all a pile of poo in any case (see Karl Popper: "The Poverty of Historicism" and "The Open Society and its Enemies"). As an example, consider someone with an extensive knowledge of the composition and actions of their favourite football team. There can be a great quantity of factual knowledge, but no need for a deep hierarchy of knowing skills.
I have taught myself a fair bit of maths, nearly always motivated by wanting to solve a particular problem in engineering. Without such a motivation, I probably would not have bothered, because it is so much hard work.
Bottom line is, if you feel that you lack mathematical knowledge and skills, is this because you need the maths to solve some mathematical problems that you are interested in (fruitful to persevere with), or is it because you lack certain paper qualifications (less fruitful due to lack of directed motivation)?
Where program size counts in a scripting language is the time taken to write the program.
We would like to estimate the time it would take write a program, as this is a measure of productivity. The problem is that the time it takes to write a program in a given language is very dependent on the skill and experience of the programmer, in relation to the language being tested. Also, some languages tend to be better than others at different tasks.
Perl has many syntactical tricks to allow common tasks to be written in a very terse form, provided you know the magic words. Python has a more regular syntax than Perl, so you do not need so much knowledge to describe a task, but you may need more words than Perl would use.
Most programmers prefer to work in the language they know best, as they can generate working code more quickly than in an unfamiliar language, even if the other language offers major advantages. However, it is always worth spending some time
investigating alternatives. I started scripting in Perl, but later switched to Python, as it is easier for me to say what I want in Python. Other people may have a different experience.
I try to assess languages by applying them to real tasks that come up at work. If the language suits my way of thinking, and has the required features (e.g. modules or libraries), I will get the job done fairly easily. I might find some features of the language attractive, if they solve
parts of the problem that would be awkward in other languages.
My point here is that a simple benchmark based on code size is almost certain to be useless for deciding which language to employ for real work.
My 80-ish father is getting along fine with KDE, kwrite, kword, etc. I built him a system for Christmas. His previous experience with personal computers was an early Apple (floppy disk only).
It probably helps that he has no preconceptions to get in the way, unlike people who compare Linux to Windows, or Open Office to Microsoft Office.
In my rather limited experience, FreeBSD boots up and shuts down far faster than Linux. Loading the
kernel and hardware probing are about the same, but the init scripts are over in a flash on FreeBSD.
I found this on 4.8-STABLE. I have recently installed 5.1-RELEASE over this, and this is also fast. 5.x has a new init script system, with dependancies.
However, to really put this to the test, I need to make sure that FreeBSD is providing all the services that Linux does. On Linux, I try to make sure that no uneccessary services are started. On FreeBSD, I need to add to the services being started to make it do the same as Linux.
Boot up time is important. Fast boot on my laptop would be very welcome. On my workstations, I experiment with new Linux kernels and FreeBSD, which requires frequent reboots. On a mission-critical server, fast shutdown and reboot reduces down-time when rebooting is the only solution to a problem.
Slashdot Mirror
I take it by "strict typing" you mean static typing? What's so great about it? Lots of server-side languages and frameworks (Python/Django, for example) are dynamically typed. I guess I'm not gettting what your point is here.
Strict/weak and static/dynamic are separate and orthogonal properties of languages.
Static typing means types are determined at compile time, as in C/C++, Java, Haskell, etc. Dynamic typing defers type checking to run time, as in Perl, Python, Erlang, etc.
Strict typing means that the type system cannot be "bent" by things like casts and unions in C, or by behind-the-scenes type conversions in Perl.
C is statically and weakly typed. Perl is dynamically and weakly typed. Python is dynamically and (fairly) strongly typed. Haskell is statically and strongly typed.
There seems to be a confusion in many posts between pure and applied mathematics. Applied mathematics is used to describe the physical world, and thus successful mathematical descriptions are discoveries. But mathematics is also used to describe mathematics. This is pure maths.
In pure maths, you can invent mathematical objects, and define their properties and relationships in a logical sense. These definitions are axioms. Then you can discover facts about this invented world. These facts are theorems. This has already been said more briefly in previous posts.
Disclaimer: I am an applied mathematician, but I appreciate the value of pure mathematical theorems related to the maths I use.
"Linear pedagogic approach".
Mathematical skills tend to depend on earlier learned skills. If you do not understand basic algebra, calculus will be nonsense to you, because the (rather difficult) ideas of calculus are usually presented in algebraic form. If you do not understand calculus, you will not understand Fourier transforms. I am sure many people fail in mathematical understanding because of missing links. Lacking these, all further mathematics that depends on these links is incomprehensible.
Contrast this with historical knowledge, or let us say general knowledge. The facts of history tend to be atomic, and the purely theoretical links between these facts are not very important, given that theories of history are probably all a pile of poo in any case (see Karl Popper: "The Poverty of Historicism" and "The Open Society and its Enemies"). As an example, consider someone with an extensive knowledge of the composition and actions of their favourite football team. There can be a great quantity of factual knowledge, but no need for a deep hierarchy of knowing skills.
I have taught myself a fair bit of maths, nearly always motivated by wanting to solve a particular problem in engineering. Without such a motivation, I probably would not have bothered, because it is so much hard work.
Bottom line is, if you feel that you lack mathematical knowledge and skills, is this because you need the maths to solve some mathematical problems that you are interested in (fruitful to persevere with), or is it because you lack certain paper qualifications (less fruitful due to lack of directed motivation)?
http://www.library.ucsf.edu/research/scholcomm/sti ckershock.html
http://library.stanford.edu/scholarly_com/data/jnl _price.pdf
This is an interesting discussion of the impact escalating scholarly journal prices:http://library.stanford.edu/scholarly_com/
(Looked (at any (Lisp code) (lately?)))
We would like to estimate the time it would take write a program, as this is a measure of productivity. The problem is that the time it takes to write a program in a given language is very dependent on the skill and experience of the programmer, in relation to the language being tested. Also, some languages tend to be better than others at different tasks.
Perl has many syntactical tricks to allow common tasks to be written in a very terse form, provided you know the magic words. Python has a more regular syntax than Perl, so you do not need so much knowledge to describe a task, but you may need more words than Perl would use.
Most programmers prefer to work in the language they know best, as they can generate working code more quickly than in an unfamiliar language, even if the other language offers major advantages. However, it is always worth spending some time investigating alternatives. I started scripting in Perl, but later switched to Python, as it is easier for me to say what I want in Python. Other people may have a different experience.
I try to assess languages by applying them to real tasks that come up at work. If the language suits my way of thinking, and has the required features (e.g. modules or libraries), I will get the job done fairly easily. I might find some features of the language attractive, if they solve parts of the problem that would be awkward in other languages.
My point here is that a simple benchmark based on code size is almost certain to be useless for deciding which language to employ for real work.It probably helps that he has no preconceptions to get in the way, unlike people who compare Linux to Windows, or Open Office to Microsoft Office.
In my rather limited experience, FreeBSD boots up and shuts down far faster than Linux. Loading the kernel and hardware probing are about the same, but the init scripts are over in a flash on FreeBSD.
I found this on 4.8-STABLE. I have recently installed 5.1-RELEASE over this, and this is also fast. 5.x has a new init script system, with dependancies.
However, to really put this to the test, I need to make sure that FreeBSD is providing all the services that Linux does. On Linux, I try to make sure that no uneccessary services are started. On FreeBSD, I need to add to the services being started to make it do the same as Linux.
Boot up time is important. Fast boot on my laptop would be very welcome. On my workstations, I experiment with new Linux kernels and FreeBSD, which requires frequent reboots. On a mission-critical server, fast shutdown and reboot reduces down-time when rebooting is the only solution to a problem.