A lot of languages (perhaps all of them) are designed to make writing programs easier. They all have different domains, and aim to simplify developing programs in these domains (C makes developing low-level programs easier, Java makes developing complex business logic easier, et al.). Perhaps other purposes are sacrificed in sake of writing and maintaining programs in an easier, more natural, less error-prone way.
Are there any languages specifically designed to make verification of source code--i.e. static analysis--easier? Of course, capability to write common programs for modern machines should also persist.
One of the design goals of Ada was to support a certian amount of formal verification. It was moderately successful, but verification didn't exactly take off like they were hoping. Luckily Ada is good for far more than that. Sadly, that hasn't helped it much either...
There's an Ada subset called Spark that keeps this alive today. Praxis sells a development suite built around it.
Are there any languages specifically designed to make verification of source code easier?
This was a vague goal of both the CLU and ML languages, but the only language design I know that takes static verification really seriously is Spark Ada.
Dijkstra's language of guarded commands (as described in Discipline of Programming) was designed to support static verification, but it was explicitly not supposed to be implemented.
Gerard Holzmann's Promela language was also designed for static analysis by the model checker SPIN, but again it's not executable.
Auditors in the E language provide a built-in means of writing code analyses within the language itself and requiring that some section of code pass some static check. You might also be interested in the related-work part of the paper.
I haven’t used it myself, so I can’t speak with any authority, but I understand that the Eiffel programming language was designed to use Code by Contracts, which would make static analysis much easier. I don’t know if that counts or not.
There is SAIL, the Static Analysis Intermediate Language or Flexibo
One has two problems in "making verification of source code easier". One is languages in which you don't do gross things such as arbitrary cases (such as C).
Another is specifying what you want to verify, for that you need a good assertions languages.
While many languages have proposed such assertions languages,
I think the EDA community has been pushing the envelope most effectively with temporal specifications. The "Property Specification Language" is a standard; you can learn more from P1850 Standard for PSL: Property Specification Language (IEEE-1850). One idea behind PSL is that you can add it to existing EDA languages; I think the EDA community has been incorporating into the EDA langauges as time goes by.
I've often wished for something like PSL to embed in conventional computer software.
Static verification is a bad start for this task. It's based on an assumption that it's possible to verify correctness of the program automatically. It's not feasible in real world, and expecting the program to check arbitrarily complex code without any hints is just plain dumb. Usually software for static verification ends up requiring hints all over source code, and in the end generates lots of false positives and false negatives. It has some niche, but that's it. (See introduction to "Types and programming languages" by Pierce)
While these kind of tools were developed by engineers for their own simple purposes, real solution have been baking in an academy. It was found that types in statically typed programming languages are equivalent to logic statements given everything goes smooth and language doesn't have some kind of bad behaviour. This is called "Curry-Howard correspondence", and the embedding of logic into types is "Brouwer-Heyting-Kolmogorov logic". The most powerful proofs are possible only in the languages with powerful types: dependent types. If we forget all this terminology for a while, this means that we can write programs that carry proofs of its own correctness, and these proofs are checked while the program gets compiled, with no executable file given in case of failure.
The positive side of this approach is that you never get any false negatives, i.e. compiled program is guaranteed to work properly according to the specification. Even without extra proofs about specification, programs in dependently-typed languages are less prone to mistakes, because divisions by zero, unhandled exceptions and overflows just never end up in an executable program.
Always writing such proofs by hand is tedious. For that there are "tactics", i.e. programs that generate proofs of correctness. These are almost equivalent to programs for static verification, but, unlike them, are required to generate formal proof.
There is a range of dependently-typed languages for different purposes: Coq, Agda, Idris, Epigram, Cayenne etc.
Tactics are implemented in Coq and probably several more languages. Also Coq is the most mature of them all, with infrastructure including libraries like Bedrock.
In case C code extraction from Coq is not enough for your requirements, you can use ATS, which is on par in performance with C.
Haskell employs weak form of Curry-Howard correspondence: it works fine, unless you start writing failing or forever-looping programs. In case your requirements are not that hard to write formal proofs, consider using Haskell.
Related
What qualifies a programming language to be called dynamic language? What sort of problems should I use a dynamic programming language to solve? What is the main difference between static programming languages and dynamic programming languages?
I don't think there is black and white here - there is a whole spectrum between dynamic and static.
Let's take two extreme examples for each side of the spectrum, and see where that takes us.
Haskell is an extreme in the static direction.
It has a powerful type system that is checked at compile time: If your program compiles it is free from common and not so common errors.
The compiled form is very different from the haskell program (it is a binary). Consequently runtime reflection and modification is hard, unless you have foreseen it. In comparison to interpreting the original, the result is potentially more efficient, as the compiler is free to do funky optimizations.
So for static languages I usually think: fairly lengthy compile-time analysis needed, type system will prevent me from making silly mistakes but also from doing some things that are actually valid, and if I want to do any manipulation of a program at runtime, it's going to be somewhat of a pain because the runtime representation of a program (i.e. its compiled form) is different from the actual language itself. Also it could be a pain to modify things later on if I have not foreseen it.
Clojure is an extreme in the dynamic direction.
It too has a type system, but at compile time there is no type checking. Many common errors can only be discovered by running the program.
Clojure programs are essentially just Clojure lists (the data structure) and can be manipulated as such. So when doing runtime reflection, you are actually processing a Clojure program more or less as you would type it - the runtime form is very close to the programming language itself. So you can basically do the same things at runtime as you could at "type time". Consequently, runtime performance may suffer because the compiler can't do many up-front optimizations.
For dynamic languages I usually think: short compilation step (basically just reading syntax), so fast and incremental development, practically no limits to what it will allow me to do, but won't prevent me from silly mistakes.
As other posts have indicated, other languages try to take more of a middle ground - e.g. static languages like F# and C# offer reflection capabilities through a separate API, and of course can offer incremental development by using clever tools like F#'s REPL. Dynamic languages sometimes offer optional typing (like Racket, Strongtalk), and generally, it seems, have more advanced testing frameworks to offset the lack of any sanity checking at compile time. Also type hints, while not checked at compile time, are useful hints to generate more efficient code (e.g. Clojure).
If you are looking to find the right tool for a given problem, then this is certainly one of the dimensions you can look at - but by itself is not likely to force a decision either way. Have a think about the other properties of the languages you are considering - is it a functional or OO or logic or ... language? Does it have a good framework for the things I need? Do I need stability and binary backwards compatibility, or can I live with some churn in the compiler? Do I need extensive tooling?Etc.
Dynamic language does many tasks at runtime where a static language would do them at compile-time.
The tasks in question are usually one or more of: type system, method dispatch and code generation.
Which also pretty much answers the questions about their usage.
There are a lot of different definitions in use, but one possible difference is:
A dynamic language typically uses dynamic typing.
A static language typically uses static typing.
Some languages are difficult to classify as either static or dynamically typed. For example, C# is traditionally regarded as a statically typed language, but C# 4.0 introduced a static type called dynamic which behaves in some ways more like a dynamic type than a static type.
What qualifies a programming language to be called dynamic language.
Dynamic languages are generally considered to be those that offer flexibility at run-time. Note that this does not necessarily conflict with static type systems. For example, F# was recently voted "favorite dynamic language on .NET" at a conference even though it is statically typed. Many people consider F# to be a dynamic language because it offers run-time features like meta-circular evaluation, a Read-Evaluate-Print-Loop (REPL) and dynamic typing (of sorts). Also, type inference means that F# code is not littered with type declarations like most statically typed languages (e.g. C, C++, Java, C# 2, Scala).
What are the problems for which I should go for dynamic language to solve.
In general, provided time and space are not of critical importance you probably always want to use languages with run-time flexibility and capabilities like run-time compilation.
This thread covers the issue pretty well:
Static/Dynamic vs Strong/Weak
The question is asked during Dynamic Languages Wizards Series - Panel on Language Design (at 24m 04s).
Answer from Jonathan Rees:
You know one when you see one
Answer from Guy Steele:
A dynamic language is one that defers as many decisions as possible to run time.
For example about array size, the number of data objects to allocate, decisions like that.
The concept is deferring until runtime, that's what I understand to be dynamic.
i have planned to develop a tool that converts a program written in a programming language (eg: Java) to a common markup language (eg: XML) and that markup code is converted to another language (eg: C#).
in simple words, it is a programming language converter that converts program written in one language to another language.
i think it is possible but i don know where to start. i wanna know the possibilities to do so and information about some existing system.
What you are trying to do is extremely hard, but if you want to know what you are up for I've listed the steps you need to follow below:
First the hard bit:
First you obtain or derive an operational semantics for your source and target languages.
Then you enhance the semantics to capture your source and target memory models.
Then you need to unify the two enhanced-semantics within a common operational model.
Then you need to define a mapping from your source languages onto the common operational model.
Then you need to define a mapping from your operational model to your target language
Step 4, as you pointed out in your question, is trivial.
Step 1 is difficult, as most languages do not have sufficiently formal semantics specified; but I recommend checking out http://lucacardelli.name/TheoryOfObjects.html as this is the best starting point for building a traditional OO semantics.
Step 2 is almost certainly impossible in general, but may be merely obscenely difficult if you are willing to sacrifice some efficiency.
Step 3 will depend on how clean the result of step 1 turned out, but is going to be anything from delicate and tricky to impossible.
Step 5 is not going to be trivial, it is effectively writing a compiler.
Ultimately, what you propose to do is impossible in general, due to the difficulties inherited in steps 1 and 2. However it should be difficult, but doable, if you are willing to: severely restrict the source language constructs supported; pretty much forget handling threads correctly; and pick two languages with sufficiently similar semantics (ie. Java and C# are ok, but C++ and anything-else is not).
It depends on what languages you want to support, but in general this is a huge & difficult task unless you plan to only support a very small subset of each language.
The real problem is that each programming languages has different features (with some areas that overlap and others that don't) and different ways of solving the same problems -- and it's pretty tricky to detect the problem the programmer is trying to solve and convert that to a new idiom. :) And think about the differences between GUIs created in different languages....
See http://xmlvm.org/ as an example (a project aimed at converting between source code of many different languages, with an XML middle-point) -- the site covers in some depth the challenges they are tackling and the compromises they take, and (if you still have any interest in this kind of project...) ask more specific followup questions.
Notice specifically what the output source code looks like -- it's not at all readable, maintainable, efficient, etc..
It is "technically easy" to produce XML for any single langauge: build a parser, construct and abstract syntax tree, and dump out that tree as XML. (I build tools that do this off-the-shelf for many languages). By technically easy, I mean that the community knows how to do this (see any compiler textbook, e.g., Aho&Ullman Dragon book). I do not mean this is a trivial exercise in terms of effort, because real languages are complicated and messy; there have been many attempts to build C++ parsers and few successes. (I have one of the successes, and it was expensive to get right).
What is really hard (and I don't try to do) is produce XML according to a single schema in which the language semantics are exposed. And without that, it will be essentially impossible to write a translator from a generic XML to an arbitrary target language. This is known as the UNCOL problem and people have been looking since 1958 for the answer. I note that the Wikipedia article seems to indicate the problem is solved, but you can't find many references to UNCOL in the literature since 1961.
The closest attempt I've seen to this is the OMG's "ASTM" model (http://www.omg.org/spec/ASTM/1.0/Beta1/); it exports XMI which is XML. But the ASTM model has lots of escapes built into it to allow langauges that it doesn't model perfectly (AFAIK, that means every language) to extend the XMI in arbitrary ways so that the language-specific information can be encoded. Consequently each language parser produces a custom version of the XMI, and thus each reader has to pretty much know about the extensions and full generality vanishes.
In the context of programming language discussion/comparison, what does the term "power" mean?
Does it have a well defined meaning? Even a poorly defined meaning?
Say if someone says "language X is more powerful than language Y" or asks the same as a question, what do they mean - or what information are they trying to find out?
It does not have a well-defined meaning. In these types of discussions, "language X is more powerful than language Y" usually means little more than "I like language X more than language Y." On the other end of the spectrum, you'll also usually have someone chime in about how any Turing-complete language can accomplish the same tasks as any other Turing-complete language, so that neither is strictly more powerful than the other.
I think a good meaning for it is expressivity. When a language is highly expressive, it means less code is required to express concepts. To me, this doesn't just mean that you have to write less code to accomplish the same tasks, but also that the code is easily readable by humans. Of course, generally (to a point), having fewer lines of code to read makes the task of reading and understanding easier for humans.
Having a "powerful" standard library comes into play here along the same lines. If a language comes equipped with thorough, complete libraries, then idiomatic code in that language will be able to benefit from the existing library code and not have to repeat or reinvent common functionality in application code. The end result is, again, having to write and read less code to accomplish the same tasks.
I keep saying "generally" and "to a point", because once a language gets too terse, it gets more difficult for humans to decipher. I suppose at this extreme, a language may still be considered "more powerful" (or even "too powerful"). So I guess I'm saying my personal interpretation of "powerful" includes some aspects of "useful" and "readable" in it as well.
C is powerful, because it is low level and gives you access to hardware. Python is powerful because you can prototype quickly. Lisp is powerful because its REPL gives you fantastic debugging opportunities. SQL is powerful because you say what you want and the DMBS will figure out the best way to do it for you. Haskell is powerful because each function can be tested in isolation. C++ is powerful because it has ten times the number of syntactic constructs that any one person ever needs or uses. APL is powerful since it can squeeze a ten-screen program into ten characters. Hell, COBOL is powerful because... why else would all the banks be using it? :)
"Powerful" has no real technical meaning, but lots of people have made proposals.
A couple of the more interesting ones:
Paul Graham wants to call a language "more powerful" if you can write the same programs in fewer lines of code (or some other sane, sensible measure of program size).
Matthias Felleisen has written a very serious theoretical study called On the Expressive Power of Programming Language.
As someone who knows and uses many programming languages, I believe that there are real differences between languages, and that "power" can be a convenient shorthand to describe ways in which one language might be better than another. Nevertheless, whenever I hear a discussion or claim that one language is more powerful than another, I tend to keep one hand firmly on my wallet.
The only meaningful way to describe "power" in a programming language is "can do what I require with the least amount of resources" where "resources" is defined as "whatever costs I'd rather not pay" and could, thus, be development time, CPU time, memory space, money, etc.
So basically the definition of "power" is purely subjective and rendered meaningless in any objective discussion.
Powerful means "high in power". "Power" is something that increases your ability to do things. "Things" vary in shape, size and other things. Loosely speaking therefore, "powerful" when applied to a programming language means that it helps you to do perform your tasks quickly and efficiently.
This makes "powerful" somewhat well defined but not constant across domains. A language powerful in one domain might be crippling in another eg. C is very powerful if you want to do systems level programming since it gives you direct access to the machine and hardware and structures that let you code much faster than you would in assembly. C compilers also produce tight code that runs fast. However, once you move to web applications, C can become very "unpowerful" and crippling since it's so much effort to get something up and running and you have to worry about a lot of extraneous details like memory etc.
Sometimes, languages are "powerful" in multiple domains. This gives them a general "powerful" tag (or badge since were are on SO here). PG's claim is that with LISP, this is the case. That might be true or might not be.
At the end of the day, "powerful" is a loaded word so you should evaluate who is saying it, why he's saying it and what it means to to your work.
There are really only two meanings people are worried about:
"Powerful" in the sense of "takes less resources (time, money, programmers, LOC, etc.) to achieve the same/better result", and "powerful" in the sense of "is capable of doing a wide range of tasks".
Some languages are extrememly resource-effective for a small range of tasks. Others are not so resource-effective but can be applied to a wide range of tasks (e.g. C, which is often used in OS development, creation of compilers and runtime libraries, and work with microcontrollers).
Which of these two meanings someone has in mind when they use the term "powerful" depends on the context (and even then is not always clear). Indeed often it is a bit of both.
Typically there are two distinct meanings:
Expressive, meaning the code tends to be very short and understandable
Low level, meaning you have very fine-grained control over the hardware.
For the most languages, these two definitions are at opposite ends of the spectrum: Python is very expressive but not very low level; C is very low level but not very expressive. Depending on which definition you pick, either language is powerful or not powerful.
nothing absolutely nothing.
To high level programmers it might mean alot of available datatypes built in. Or maybe abstractions to easily create or follow Design Patterns.
Paul Graham is a very high level guy here is what he has to say:
http://www.paulgraham.com/avg.html
Java guys might tell you something about portability, the power to reach every platform.
C/UNIX programmers may tell you that its speed and efficiency, complete control over every inch of memory.
VHDL/Verilog programmers will tell you its complete control over every clock and gate so as to not waste any electricity or time.
But in my opinion a "powerful language" supports all of the features for you to complete your task. Documentation may be important, or perhaps it is portability, or the ability to do graphics. It could be anything, writing a gui from Assembly is just stupid, so is trying to design an embedded processor in flash.
Choosing a language that suits your needs perfectly will always feel like power.
I view the term as marketing fluff, no one well-defined meaning.
If you consider, say, Assembler, C, and C++. On occasions one drops from C++ "down" to C for particualr needs, and in turn from C down to assembler. So that make assembler the most powerful because it's the only language that can do everything. Or, to argue the other way, a single line of C++ code can replace several of C (hiding polymorphic dispatch via function pointers for example) and a single line of C replaces many of assembler. So C++ is more powerful because one line does "more".
I think the term had some currency when products such as early databases and spreadsheets had in-built languages, some quite restricted. So vendors would tout their language as being "powerful" because it was less restricted.
It can have several meanings. In the very basic sense there's power as far as what is computable. In that sense the most powerful languages are Turing Complete which includes pretty much every general purpose programming language (as opposed to most markup languages and domain specific languages which are often not Turing complete).
In a more pragmatic sense it often refers to how concisely (and readably) you can do certain things. Basically how easy is it to do certain tasks in one language compared to another.
What language is more powerful (besides being somewhat subjective) depends heavily on what you're trying to do. If your requirements are to get something running on a small device with 64k of memory you're likely not going to be using Java. Most likely the right language would be C or C++ (or if you're really hard core assembly). If you need a very simple CRUD app done in 1 day, maybe something like Ruby On Rails would be the way to go (I know Rails is a framework and Ruby is the language, but these days what libraries and frameworks are available factor greatly into picking a language)
I think that, perhaps coincidentally, the physics definition of power is relevant here: "The rate at which work is performed."
Of course, a toaster does not perform very quickly the work of putting out fires. Similarly, the power of a programming language is not universal, but specific to the domain or task to which it is being applied. C is a powerful language for writing device drivers or implementations of higher-level languages; Python is a powerful language for writing general-purpose applications; XPath is a powerful language for writing queries on structured data sets.
So given a problem domain, the power of a language can be said to be the rate at which a competent programmer is able to use it to solve problems in that domain.
A precise answer can be tried to reach, by not assuming that the elements that define "powerful" (in the context of languages) come from so many dimensions.
See how many could be, and a lot will be missing:
runtime speed
code size
expressiveness
supported paradigms
development / debugging time
domain specialization
standard libs
codebase
toolchain ecosystem
portability
community
support / documentation
popularity
(add more here)
These and more parameters draw together X picture of how "programming in some language" would be like at X level. That will be only the definition, though, the only real knowledge comes with the actual practice of using the language, but i digress.
The question comes down to which parameter will represent the intrinsic quality of a language. If you refer to a language in itself, its ultimate, intrinsic purpose is "express things", and thus the most representative parameter is rightfully expressiveness, and is also one that resonates frequently when someone talks about how powerful a language is.
At the moment you try to widen the question/answer to cover more than the expressiveness of the language "as a language, as a tongue", you are more talking about different kinds of "environment", social environment, development environment, commercial environment, etc.
Depending of the complexity of the environment to be defined you'll have to mix more parameters that come from multiple, vast, overlapping and sometimes contradictory dimensions, and eventually the point of getting the definition will be lost or the question will have to be narrowed.
This approximation still won't answer "what is an expressive language", but, again, a common understanding are the definitions that Vineet well points out in its answer, and Forest remarks in the comments. I agree, for me "expression" is "conveying meaning".
I remember many instructors in college calling whatever language they were teaching "powerful".
Leads me to think:
Powerful = a relative term comparing the latest way to code something vs. the original or previous way.
I find it useless to use the word "powerful" in regards to discussing anything software related. Every time my professor in college would introduce a new concept such as polymorphism he would say "so this is a really powerful feature". After a while I got annoyed. If everything is powerful then nothing is. It's all the same. You can write code to do anything. Does is really matter how much code is required to do it? You can say it's short or efficient but powerful is just useless. Nuclear energy is powerful. Code is words.
I think that power would normally refer to how quickly it can process data, for example I found that in python as soon as a list exceeds a length of approx. 2000 it becomes unbearably slow whereas in C++ a list can easily contain 20,000 entries without doing so.
Jon Skeet posted this blog post, in which he states that he is going to be asking why the dynamic part of languages are so good. So i thought i'd preemptively ask on his behalf: What makes them so good?
The two fundamentally different approaches to types in programming languages are static types and dynamic types. They enable very different programming paradigms and they each have their own benefits and drawbacks.
I'd highly recommend Chris Smith's excellent article What to Know Before Debating Type Systems for more background on the subject.
From that article:
A static type system is a mechanism by which a compiler examines source code and assigns labels (called "types") to pieces of the syntax, and then uses them to infer something about the program's behavior. A dynamic type system is a mechanism by which a compiler generates code to keep track of the sort of data (coincidentally, also called its "type") used by the program. The use of the same word "type" in each of these two systems is, of course, not really entirely coincidental; yet it is best understood as having a sort of weak historical significance. Great confusion results from trying to find a world view in which "type" really means the same thing in both systems. It doesn't. The better way to approach the issue is to recognize that:
Much of the time, programmers are trying to solve the same problem with
static and dynamic types.
Nevertheless, static types are not limited to problems solved by dynamic
types.
Nor are dynamic types limited to problems that can be solved with
static types.
At their core, these two techniques are not the same thing at all.
The main thing is that you avoid a lot of redundancy that comes from making the programmer "declare" this, that, and the other. A similar advantage could be obtained through type inferencing (boo does that, for example) but not quite as cheaply and flexibly. As I wrote in the past...:
complete type checking or inference
requires analysis of the whole
program, which may be quite
impractical -- and stops what Van Roy
and Haridi, in their masterpiece
"Concepts, Techniques and Models of
Computer Programming", call "totally
open programming". Quoting a post of
mine from 2004: """ I love the
explanations of Van Roy and Haridi, p.
104-106 of their book, though I may or
may not agree with their conclusions
(which are basically that the
intrinsic difference is tiny -- they
point to Oz and Alice as interoperable
languages without and with static
typing, respectively), all the points
they make are good. Most importantly,
I believe, the way dynamic typing
allows real modularity (harder with
static typing, since type discipline
must be enforced across module
boundaries), and "exploratory
computing in a computation model that
integrates several programming
paradigms".
"Dynamic typing is recommended", they
conclude, "when programs must be as
flexible as possible". I recommend
reading the Agile Manifesto to
understand why maximal flexibility is
crucial in most real-world
application programming -- and
therefore why, in said real world
rather than in the more academic
circles Dr. Van Roy and Dr. Hadidi
move in, dynamic typing is generally
preferable, and not such a tiny issue
as they make the difference to be.
Still, they at least show more
awareness of the issues, in devoting 3
excellent pages of discussion about
it, pros and cons, than almost any
other book I've seen -- most books
have clearly delineated and preformed
precedence one way or the other, so
the discussion is rarely as balanced
as that;).
I'd start with recommending reading Steve Yegge's post on Is Weak Typing Strong Enough, then his post on Dynamic Languages Strike Back. That ought to at least get you started!
Let's do a few advantage/disadvantage comparisons:
Dynamic Languages:
Type decisions can be changed with minimal code impact.
Code can be written/compiled in isolation. I don't need an implementation or even formal description of the type to write code.
Have to rely on unit tests to find any type errors.
Language is more terse. Less typing.
Types can be modified at runtime.
Edit and continue is much easier to implement.
Static Languages:
Compiler tells of all type errors.
Editors can offer prompts like Intellisense much more richly.
More strict syntax which can be frustrating.
More typing is (usually) required.
Compiler can do better optimization if it knows the types ahead of time.
To complicate things a little more, consider that languages such as C# are going partially dynamic (in feel anyway) with the var construct or languages like Haskell that are statically typed but feel dynamic because of type inference.
Dynamic programming languages basically do things at runtime that other languages do at Compile time. This includes extension of the program, by adding new code, by extending objects and definitions, or by modifying the type system, all during program execution rather than compilation.
http://en.wikipedia.org/wiki/Dynamic_programming_language
Here are some common examples
http://en.wikipedia.org/wiki/Category:Dynamic_programming_languages
And to answer your original question:
They're slow, You need to use a basic text editor to write them - no Intellisense or Code prompts, they tend to be a big pain in the ass to write and maintain. BUT the most famous one (javascript) runs on practically every browser in the world - that's a good thing I guess. Lets call it 'broad compatibility'. I think you could probably get a dynamic language interpretor for most operating systems, but you certainly couldn't get a compiler for non dynamic languages for most operating systems.
At the risk of sounding naive, I ask this question in search of a deeper understanding of the concept of programming languages in general. I write this question for my own edification and the edification of others.
What is a useful definition of a computer programming language and what are its basic and necessary components? What are the key features that differentiate languages (functional, imperative, declarative, object oriented, scripting, etc...)?
One way to think about this question. Imagine you are looking at the hardware of a modern desktop or laptop computer. Assume, that the C language or any of its variants do not exist. How would you describe to others all the things needed to make the computer expressive and functional in terms of what we expect of personal computers today?
Tangentially related, what is it about computer languages that allow other languages to exist? For example take a scripting language like Javascript, Perl, or PHP. I assume part of the definition of these is that there is an interpreter most likely implemented in C or C++ at some level. Is it possible to write an interpreter for Javascript in Javascript? Is this a requirement for a complete language? Same for Perl, PHP, etc?
I would be satisfied with a list of concepts that can be looked up or researched further.
Like any language, programming languages are simply a communication tool for expressing and conveying ideas. In this case, we're translating our ideas of how software should work into a structured and methodical form that computers (as well as other humans who know the language, in most cases) can read and understand.
What is a useful definition of a computer programming language and what are its basic and necessary components?
I would say the defining characteristic of a programming language is as follows: things written in that language are intended to eventually be transformed into something that is executed. Thus, pseudocode, while perhaps having the structure and rigor of a programming language, is not actually a programming language. Likewise, UML can express many powerful ideas in an abstract manner just like a programming language can, but it falls short because people don't generally write UML to be executed.
How would you describe to others all the things needed to make the computer expressive and functional in terms of what we expect of personal computers today?
Even if the word "programming language" wasn't part of the shared vocabulary of the group I was talking to, I think it would be obvious to the others that we'd need a way to communicate with the computer. Just as no one expects a car to drive itself (yet!) without external instructions in the form of interaction with the steering wheel and pedals, no one could expect the hardware to function without being told what to do. As noted above, a programming language is the conduit through which we can make that communication happen.
Tangentially related, what is it about computer languages that allow other languages to exist?
All useful programming languages have a property called Turing completeness. If one language in the Turing-complete set can do something, then any of them can; they are said to be computationally equivalent.
However, just because they're equally "powerful" doesn't mean they're equally nice to work with for humans. This is why many people are willing to sacrifice the unparalleled micromanagement you get from writing assembly code in exchange for the expressiveness and power you get with higher-level languages, like Ruby, Python, or C#.
Is it possible to write an interpreter for Javascript in Javascript? Is this a requirement for a complete language? Same for Perl, PHP, etc?
Since there is a Javascript interpreter written in C, it follows that it must be possible to write a Javascript interpreter in Javascript, since both are Turing-complete. However, again, note that Turing-completeness says nothing about how hard it is to do something in one language versus another -- only whether it is possible to begin with. Your Javascript-interpreter-inside-Javascript might well be horrendously inefficient, consume absurd amounts of memory, require enormous processing power, and be a hideously ugly hack. But Turing-completeness guarantees it can be done!
While this doesn't directly answer your question, I am reminded of the Revenge of the Nerds essay by Paul Graham about the evolution of programming languages. It's certainly an interesting place to start your investigation.
Not a definition, but I think there are essentially two strands of development in programming languages:
Those working their way up from what the machine can do to something more expressive and less tied to the machine (Assembly, Fortran, C, C++, Java, ...)
Those going down from some mathematical or theoretical computer science concept of computation to something implementable on a real machine (Lisp, Prolog, ML, Haskell, ...)
Of course, in reality the picture is not as neat, and both strands influence each other by borrowing the best ideas.
Slightly long rant ahead.
A computer language is actually not all that different from a human language. Both are used to express ideas and concepts in commonly understood terms. Among different human languages there are syntactic differences, but you can express the same thing in every language (does that make human languages Turing complete? :)). Some languages are better suited for expressing certain things than others.
For example, although technically not completely correct, the Inuit language seems quite suited to describe various kinds of snow. Japanese in my experience is very suitable for expressing ones feelings and state of mind thanks to a large, concise vocabulary in that area. German is pretty good for being very precise thanks to largely unambiguous grammar.
Different programming languages have different specialities as well, but they mostly differ in the level of detail required to express things. The big difference between human and programming languages is mostly that programming languages lack a lot of vocabulary and have very few "grammatical" rules. With libraries you can extend the vocabulary of a language though.
For example:
Make me coffee.
Very easy to understand for a human, but only because we know what each of the words mean.
coffee : a drink made from the roasted and ground beanlike seeds of a tropical shrub
drink : a liquid that can be swallowed
swallow : cause or allow to pass down the throat
... and so on and so on
We know all these definitions by heart, but we had to learn them at some point.
In the same way, a computer can be "taught" to "understand" words as well.
Coffee::make()->giveTo($me);
This could be a perfectly valid expression in a computer language. If the computer "knows" what Coffee, make() and giveTo() means and if $me is defined. It expresses the same idea as the English sentence, just with a different, more rigorous syntax.
In a different environment you'd have to say slightly different things to get the same outcome. In Japanese for example you'd probably say something like:
コーヒーを作ってもらっても良いですか？
Kōhī o tsukuttemoratte mo ii desu ka?
Which would roughly translate to:
if ($Person->isAgreeable('Coffee::make()')) {
return $Person->return(Coffee::make());
}
Same idea, same outcome, but the $me is implied and if you don't check for isAgreeable first you may get a runtime error. In computer terms that would be somewhat analogous to Ruby's implied behaviour of returning the result of the last expression ("grammatical feature") and checking for available memory first (environmental necessity).
If you're talking to a really slow person with little vocabulary, you probably have to explain things in a lot more detail:
Go to the kitchen.
Take a pot.
Fill the pot with water.
...
Just like Assembler. :o)
Anyway, the point being, a programming language is actually a language just like a human language. Their syntax is different and specialized for the problem domain (logic/math) and the "listener" (computers), but they're just ways to transport ideas and concepts.
EDIT:
Another point about "optimization for the listener" is that programming languages try to eliminate ambiguity. The "make me coffee" example could, technically, be understood as "turn me into coffee". A human can tell what's meant intuitively, a computer can't. Hence in programming languages everything usually has one and one meaning only. Where it doesn't you can run into problems, the "+" operator in Javascript being a common example.
1 + 1 -> 2
'1' + '1' -> '11'
See "Programming Considered as a Human Activity." EWD 117.
http://www.cs.utexas.edu/~EWD/transcriptions/EWD01xx/EWD117.html
Also See http://www.csee.umbc.edu/331/current/notes/01/01introduction.pdf
Human expression which:
describes mathematical functions
makes the computer turn switches on and off
This question is very broad. My favorite definition is that a programming language is a means of expressing computations
Precisely
At a high level
In ways we can reason about them
By computation I mean what Turing and Church meant: the Turing machine and the lambda calculus have equivalent expressive power (which is a theorem), and the Church-Turing hypothesis (which is a conjecture) says roughly that there's no more powerful notion of computation out there. In other words, the kinds of computations that can be expressed in any programming languages are at best the kinds that can be expressed using Turing machines or lambda-calculus programs—and some languages will be able to express only a subset of those calculations.
This definition of computation also encompasses your friendly neighborhood hardware, which is pretty easy to simulate using a Turing machine and even easier to simulate using the lambda calculus.
Expressing computations precisely means the computer can't wiggle out of its obligations: if we have a particular computation in mind, we can use a programming language to force the computer to perform that computation. (Languages with "implementation defined" or "undefined" constructs make this task more difficult. Programmers using these languages are often willing to settle for—or may be unknowingly settling for—some computation that is only closely related to the computation they had in mind.)
Expressing computation at a high level is what programming langauges are all about. An important reason that there are so many different programming languages out there is that there are so many different high-level ways of thinking about problems. Often, if you have an important new class of problems to solve, you may be best off creating a new programming language. For example, Larry Wall's writing suggests that solving a class of problems called "systems administration" was a motivation for him to create Perl.
(Another reason there are so many different programming languages out there is that creating a new language is a lot of fun, and anyone can learn to do it.)
Finally, many programmers want languages that make it easy to reason about programs. For example, today a student of mine implemented a new algorithm that made his program run over six times faster. He had to reason very carefully about the contents of C arrays to make sure that the new algorithm would do the same job the old one did. Luckily C has decent tools for reasoning about programs, for example:
A change in a[i] cannot affect the value of a[i-1].
My student also applied a reasoning principle that isn't valid in C:
The sum of of a sequence unsigned integers will be at least as large as any integer in the sequence.
This isn't true in C because the sum might overflow. One reason some programmers prefer languages like Standard ML is that in SML, this reasoning principle is always valid. Of languages in wide use, probably Haskell has the strongest reasoning principles Richard Bird has developed equational reasoning about programs to a high art.
I will not attempt to address all the tangential details that follow your opening question. But I hope you will get something out of an answer that aims to give a deeper understanding, as you asked, of a fundamental question about programming languages.
One thing a lot of "IT" types forget is that there are 2 types of computer programming languages:
Software programming languages: C, Java, Perl, COBAL, etc.
Hardware programming languages: VHDL, Verilog, System Verilog, etc.
Interesting.
I'd say the defining feature of a programming language is the ability to make decisions based on input. Effectively, if and goto. Everything else is lots and lots of syntactic sugar. This is the idea that spawned Brainfuck, which is actually remarkably fun to (try to) use.
There are places where the line blurs; for example, I doubt people would consider XSLT to really be a programming language, but it's Turing-complete. I've even solved a Project Euler problem with it. (Very, very slowly.)
Three main properties of languages come to mind:
How is it run? Is it compiled to bare metal (C), compiled to mostly bare metal with some runtime lookup (C++), run on a JIT virtual machine (Java, .NET), bytecode-interpreted (Perl), or purely interpreted (uhh..)? This doesn't comment much on the language itself, but speaks to how portable the code may be, what sort of speed I might expect (and thus what broad classes of tasks would work well), and sometimes how flexible the language is.
What paradigms does it support? Procedural? Functional? Is the standard library built with classes or functions? Is there reflection? Is there, ideally, support for pretty much whatever I want to do?
How can I represent my data? Are there arrays, and are they fixed-size or not? How easy is it to use strings? Are there structs or hashes built in? What's the type system like? Are there objects? Are they class-based or prototype-based? Is everything an object, or are there primitives? Can I inherit from built-in objects?
I realize the last one is a very large collection of potential questions, but it's all related in my mind.
I imagine rebuilding the programming language landscape entirely from scratch would work pretty much how it did the first time: iteratively. Start with assembly, the list of direct commands the processor understands, and wrap it with something a bit easier to use. Repeat until you're happy.
Yes, you can write a Javascript interpreter in Javascript, or a Python interpreter in Python (see: PyPy), or a Python interpreter in Javascript. Such languages are called self-hosting. Have a look at Perl 6; this has been a goal for its main implementation from the start.
Ultimately, everything just has to translate to machine code, not necessarily C. You can write D or Fortran or Haskell or Lisp if you want. C just happens to be an old standard. And if you write a compiler for language Foo that can ultimately spit out machine code, by whatever means, then you can rewrite that compiler in Foo and skip the middleman. Of course, if your language is purely interpreted, this will probably result in a stack overflow...
As a friend taught me about computer languages, a language is a world. A world of communication with that machine. It is world for implementing ideas, algorithms, functionality, as Alonzo and Alan described. It is the technical equivalent of the mathematical structures that the aforementioned scientists built. It is a language with epxressions and also limits. However, as Ludwig Wittgenstein said "The limits of my language mean the limits of my world", there are always limitations and that's how one chooses it's language that fits better his needs.
It is a generic answer... some thoughts actually and less an answer.
There are many definitions to this but what I prefer is:
Computer programming is programming that helps to solve a particular technical task/problem.
There are 3 key phrases to look out for:
You: Computer will do what you (Programmer) told it to do.
Instruct: Instruction is given to the computer in a language that it can understand. We will discuss that below.
Problem: At the end of the day computers are tools (Complex). They are there to make out life simpler.
The answer can be lengthy but you can find more about computer programming