Scheme offers a primitive call-with-current-continuation, commonly abbreviated call/cc, which has no equivalent in the ANSI Common Lisp specification (although there are some libraries that try to implement them).
Does anybody know the reason why the decision of not creating a similar primitive in the ANSI Common Lisp specification was made?
Common Lisp has a detailed file compilation model as part of the standard language. The model supports compiling the program to object files in one environment, and loading them into an image in another environment. There is nothing comparable in Scheme. No eval-when, or compile-file, load-time-value or concepts like what is an externalizable object, how semantics in compiled code must agree with interpreted code. Lisp has a way to have functions inlined or not to have them inlined, and so basically you control with great precision what happens when a compiled module is re-loaded.
By contrast, until a recent revision of the Scheme report, the Scheme language was completely silent on the topic of how a Scheme program is broken into multiple files. No functions or macros were provided for this. Look at R5RS, under 6.6.4 System Interface. All that you have there is a very loosely defined load function:
optional procedure: (load filename)
Filename should be a string naming an existing file containing Scheme source code. The load procedure reads expressions and definitions from the file and evaluates them sequentially. It is unspecified whether the results of the expressions are printed. The load procedure does not affect the values returned by current-input-port and current-output-port. Load returns an unspecified value.
Rationale: For portability, load must operate on source files. Its operation on other kinds of files necessarily varies among implementations.
So if that is the extent of your vision about how applications are built from modules, and all details beyond that are left to implementors to work out, of course the sky is the limit regarding inventing programming language semantics. Note in part the Rationale part: if load is defined as operating on source files (with all else being a bonus courtesy of the implementors) then it is nothing more than a textual inclusion mechanism like #include in the C language, and so the Scheme application is really just one body of text that is physically spread into multiple text files pulled together by load.
If you're thinking about adding any feature to Common Lisp, you have to think about how it fits into its detailed dynamic loading and compilation model, while preserving the good performance that users expect.
If the feature you're thinking of requires global, whole-program optimization (whereby the system needs to see the structural source code of everything) in order that users' programs not run poorly (and in particular programs which don't use that feature) then it won't really fly.
Specifically with regard to the semantics of continuations, there are issues. In the usual semantics of a block scope, once we leave a scope and perform cleanup, that is gone; we cannot go back to that scope in time and resume the computation. Common Lisp is ordinary in that way. We have the unwind-protect construct which performs unconditional cleanup actions when a scope terminates. This is the basis for features like with-open-file which provides an open file handle object to a block scope and ensures that this is closed no matter how the block scope terminates. If a continuation escapes from that scope, that continuation no longer has a valid file. We cannot simply not close the file when we leave the scope because there is no assurance that the continuation will ever be used; that is to say, we have to assume that the scope is in fact being abandoned forever and clean up the resource in a timely way. The band-aid solution for this kind of problem is dynamic-wind, which lets us add handlers on entry and exit to a block scope. Thus we can re-open the file when the block is restarted by a continuation. And not only re-open it, but actually position the stream at exactly the same position in the file and so on. If the stream was half way through decoding some UTF-8 character, we must put it into the same state. So if Lisp got continuations, either they would be broken by various with- constructs that perform cleanup (poor integration) or else those constructs would have to acquire much more hairy semantics.
There are alternatives to continuations. Some uses of continuations are non-essential. Essentially the same code organization can be obtained with closures or restarts. Also, there is a powerful language/operating-system construct that can compete with the continuation: namely, the thread. While continuations have aspects that are not modeled nicely by threads (and not to mention that they do not introduce deadlocks and race conditions into the code) they also have disadvantages compared to threads: like the lack of actual concurrency for utilization of multiple processors, or prioritization. Many problems expressible with continuations can be expressed with threads almost as easily. For instance, continuations let us write a recursive-descent parser which looks like a stream-like object which just returns progressive results as it parses. The code is actually a recursive descent parser and not a state machine which simulates one. Threads let us do the same thing: we can put the parser into a thread wrapped in an "active object", which has some "get next thing" method that pulls stuff from a queue. As the thread parsers, instead of returning a continuation, it just throws objects into a queue (and possibly blocks for some other thread to remove them). Continuation of execution is provided by resuming that thread; its thread context is the continuation. Not all threading models suffer from race conditions (as much); there is for instance cooperative threading, under which one thread runs at a time, and thread switches only potentially take place when a thread makes an explicit call into the threading kernel. Major Common Lisp implementations have had light-weight threads (typically called "processes") for decades, and have gradually moved toward more sophisticated threading with multiprocessing support. The support for threads lessens the need for continuations, and is a greater implementation priority because language run-times without thread support are at technological disadvantage: inability to take full advantage of the hardware resources.
This is what Kent M. Pitman, one of the designers of Common Lisp, had to say on the topic: from comp.lang.lisp
The design of Scheme was based on using function calls to replace most common control structures. This is why Scheme requires tail-call elimination: it allows a loop to be converted to a recursive call without potentially running out of stack space. And the underlying approach of this is continuation-passing style.
Common Lisp is more practical and less pedagogic. It doesn't dictate implementation strategies, and continuations are not required to implement it.
Common Lisp is the result of a standardization effort on several flavors of practical (applied) Lisps (thus "Common"). CL is geared towards real life applications, thus it has more "specific" features (like handler-bind) instead of call/cc.
Scheme was designed as small clean language for teaching CS, so it has the fundamental call/cc which can be used to implement other tools.
See also Can call-with-current-continuation be implemented only with lambdas and closures?
Related
Scala native has been recently released, but the garbage collector they used (for now) is extremely rudimentary and makes it not suitable for serious use.
So I wonder: why not just transpile Scala to Go (a la Scala.js)? It's going to be a fast, portable runtime. And their GC is getting better and better. Not to mention the inheritance of a great concurrency model: channels and goroutines.
So why did scala-native choose to go so low level with LLVM?
What would be the catch with a golang transpiler?
There are two kinds of languages that are good targets for compilers:
Languages whose semantics closely match the source language's semantics.
Languages which have very low-level and thus very general semantics (or one might argue: no semantics at all).
Examples for #1 include: compiling ECMAScript 2015 to ECMAScript 5 (most language additions were specifically designed as syntactic sugar for existing features, you just have to desugar them), compiling CoffeeScript to ECMAScript, compiling TypeScript to ECMAScript (basically, after type checking, just erase the types and you are done), compiling Java to JVM byte code, compiling C♯ to CLI CIL bytecode, compiling Python to CPython bytecode, compiling Python to PyPy bytecode, compiling Ruby to YARV bytecode, compiling Ruby to Rubinius bytecode, compiling ECMAScript to SpiderMonkey bytecode.
Examples for #2 include: machine code for a general purpose CPU (RISC even more so), C--, LLVM.
Compiling Scala to Go fits neither of the two. Their semantics are very different.
You need either a language with powerful low-level semantics as the target language, so that you can build your own semantics on top, or you need a language with closely matching semantics, so that you can map your own semantics into the target language.
In fact, even JVM bytecode is already too high-level! It has constructs such as classes that do not match constructs such as Scala's traits, so there has to be a fairly complex encoding of traits into classes and interfaces. Likewise, before invokedynamic, it was actually pretty much impossible to represent dynamic dispatch on structural types in JVM bytecode. The Scala compiler had to resort to reflection, or in other words, deliberately stepping outside of the semantics of JVM bytecode (which resulted in a terrible performance overhead for method dispatch on structural types compared to method dispatch on other class types, even though both are the exact same thing).
Proper Tail Calls are another example: we would like to have them in Scala, but because JVM bytecode is not powerful enough to express them without a very complex mapping (basically, you have to forego using the JVM's call stack altogether and manage your own stack, which destroys both performance and Java interoperability), it was decided to not have them in the language.
Go has some of the same problems: in order to implement Scala's expressive non-local control-flow constructs such as exceptions or threads, we need an equally expressive non-local control-flow construct to map to. For typical target languages, this "expressive non-local control-flow construct" is either continuations or the venerable GOTO. Go has GOTO, but it is deliberately limited in its "non-localness". For writing code by humans, limiting the expressive power of GOTO is a good thing, but for a compiler target language, not so much.
It is very likely possible to rig up powerful control-flow using goroutines and channels, but now we are already leaving the comfortable confines of just mapping Scala semantics to Go semantics, and start building Scala high-level semantics on top of Go high-level semantics that weren't designed for such usage. Goroutines weren't designed as a general control-flow construct to build other kinds of control-flow on top of. That's not what they're good at!
So why did scala-native choose to go so low level with LLVM?
Because that's precisely what LLVM was designed for and is good at.
What would be the catch with a golang transpiler?
The semantics of the two languages are too different for a direct mapping and Go's semantics are not designed for building different language semantics on top of.
their GC is getting better and better
So can Scala-native's. As far as I understand, the choice for current use of Boehm-Dehmers-Weiser is basically one of laziness: it's there, it works, you can drop it into your code and it'll just do its thing.
Note that changing the GC is under discussion. There are other GCs which are designed as drop-ins rather than being tightly coupled to the host VM's object layout. E.g. IBM is currently in the process of re-structuring J9, their high-performance JVM, into a set of loosely coupled, independently re-usable "runtime building blocks" components and releasing them under a permissive open source license.
The project is called "Eclipse OMR" (source on GitHub) and it is already production-ready: the Java 8 implementation of IBM J9 was built completely out of OMR components. There is a Ruby + OMR project which demonstrates how the components can easily be integrated into an existing language runtime, because the components themselves assume no language semantics and no specific memory or object layout. The commit which swaps out the GC and adds a JIT and a profiler clocks in at just over 10000 lines. It isn't production-ready, but it boots and runs Rails. They also have a similar project for CPython (not public yet).
why not just transpile Scala to Go (a la Scala.js)?
Note that Scala.JS has a lot of the same problems I mentioned above. But they are doing it anyway, because the gain is huge: you get access to every web browser on the planet. There is no comparable gain for a hypothetical Scala.go.
There's a reason why there are initiatives for getting low-level semantics into the browser such as asm.js and WebAssembly, precisely because compiling a high-level language to another high-level language always has this "semantic gap" you need to overcome.
In fact, note that even for lowish-level languages that were specifically designed as compilation targets for a specific language, you can still run into trouble. E.g. Java has generics, JVM bytecode doesn't. Java has inner classes, JVM bytecode doesn't. Java has anonymous classes, JVM bytecode doesn't. All of these have to be encoded somehow, and specifically the encoding (or rather non-encoding) of generics has caused all sorts of pain.
I’ve been working with Scala language for a few months and I’ve already created couple projects in Scala. I’ve found Scala REPL (at least its IntelliJ worksheet implementation) is quite convenient for quick development. I can write code, see what it does and it’s nice. But I do the procedure only for functions (not whole program). I can’t start my application and change it on spot. Or at least I don’t know how (so if you know you are welcome to give me piece of advice).
Several days ago my associate told me about Clojure REPL. He uses Emacs for development process and he can change code on spot and see results without restarting. For example, he starts the process and if he changes implementation of a function, his code will change his behavior without restart. I would like to have the same thing with Scala language.
P.S. I want to discuss neither which language is better nor does functional programming better than object-oriented one. I want to find a good solution. If Clojure is the better language for the task so let it be.
The short answer is that Clojure was designed to use a very simple, single pass compiler which reads and compiles a single s-expression or form at a time. For better or worse there is no global type information, no global type inference and no global analysis or optimization. Clojure uses clojure.lang.Var instances to create global bindings through a series of hashmaps from textual symbols to transactional values. def forms all create bindings at global scope in this global binding map. So where in Scala a "function" (method) will be resolved to an instance or static method on a given JVM class, in Clojure a "function" (def) is really just a reference to an entry in the table of var bindings. When a function is invoked, there isn't a static link to another class, instead the var is reference by symbolic name, then dereferenced to get an instance of a clojure.lang.IFn object which is then invoked.
This layer of indirection means that it is possible to re-evaluate only a single definition at a time, and that re-evaluation becomes globaly visible to all clients of the re-defined var.
In comparison, when a definition in Scala changes, scalac must reload the changed file, macroexpand, type infer, type check, and compile. Then due to the semantics of classloading on the JVM, scalac must also reload all classes which depend on methods in the class which changed. Also all values which are instances of the changed class become trash.
Both approaches have their strengths and weaknesses. Obviously Clojure's approach is simpler to implement, however it pays an ongoing cost in terms of performance due to continual function lookup operations forget correctness concerns due to lack of static types and what have you. This is arguably suitable for contexts in which lots of change is happening in a short timeframe (interactive development) but is less suitable for context when code is mostly static (deployment, hence Oxcart). some work I did suggests that the slowdown on Clojure programs from lack of static method linking is on the order of 16-25%. This is not to call Clojure slow or Scala fast, they just have different priorities.
Scala chooses to do more work up front so that the compiled application will perform better which is arguably more suitable for application deployment when little or no reloading will take place, but proves a drag when you want to make lots of small changes.
Some material I have on hand about compiling Clojure code more or less cronological by publication order since Nicholas influenced my GSoC work a lot.
Clojure Compilation [Nicholas]
Clojure Compilation: Full Disclojure [Nicholas]
Why is Clojure bootstrapping so slow? [Nicholas]
Oxcart and Clojure [me]
Of Oxen, Carts and Ordering [me]
Which I suppose leaves me in the unhappy place of saying simply "I'm sorry, Scala wasn't designed for that the way Clojure was" with regards to code hot swapping.
Most people agree that LISP helps to solve problems that are not well defined, or that are not fully understood at the beginning of the project.
"Not fully understood"" might indicate that we don't know what problem we are trying to solve, so the developer refines the problem domain continuously. But isn't this process language independent?
All this refinement does not take away the need for, say, developing algorithms/solutions for the final problem that does need to be solved. And that is the actual work.
So, I'm not sure what advantage LISP provides if the developer has no idea where he's going i.e. solving a problem that is not finalised yet.
Lisp (not "LISP") has a number of advantages when you're facing problems that are not well-defined. First of all, you have a REPL where you can quickly experiment with -- that helps in sketching out quick functions and trying to play with them, leading to a very rapid development cycle. Second, having a dynamically typed language is working well in this context too: with a statically typed language you need to "design more" before you begin, and changing the design leads to changing more code -- in contrast, with Lisps you just write the code and the data it operates on can change as needed. In addition to these, there's the usual benefits of a functional language -- one with first class lambda functions, etc (eg, garbage collection).
In general, these advantage have been finding their way into other languages. For example, Javascript has everything that I listed so far. But there is one more advantage for Lisps that is still not present in other languages -- macros. This is an important tool to use when your problem calls for a domain specific language. Basically, in Lisp you can extend the language with constructs that are specific to your problem -- even if these constructs lead to a completely different language.
Finally, you need to plan ahead for what happens when the code becomes more than a quick experiment. In this case you want your language to cope with "growing scripts into applications" -- for example, having a module system means that you can get a more "serious"
application. For example, in Racket you can get your solution separated into such modules, where each can be written in its own language -- it even has a statically typed language which makes it possible to start with a dynamically typed development cycle and once the code becomes more stable and/or big enough that maintenance becomes difficult, you can switch some modules into the static language and get the usual benefits from that. Racket is actually unique among Lisps and Schemes in this kind of support, but even with others the situation is still far more advanced than in non-Lisp languages.
In AI (Artificial Intelligence) historically Lisp was seen as the AI assembly language. It was used to build higher-level languages which help to work with the problem domain in a more direct way. Many of these domains need a lot of 'knowledge' for finding usable answers.
A typical example is an expert system for, say, oil exploration. The expert system gets as inputs (geological) observations and gives information about the chances to find oil, what kind of oil, in what depths, etc. To do that it needs 'expert knowledge' how to interpret the data. When you start such a project to develop such an expert system it is typically not clear what kind of inferences are needed, what kind of 'knowledge' experts can provide and how this 'knowledge' can be written down for a computer.
In this case one typically develops new languages on top of Lisp and you are not working with a fixed predefined language.
As an example see this old paper about Dipmeter Advisor, a Lisp-based expert system developed by Schlumberger in the 1980s.
So, Lisp does not solve any problems. But it was originally used to solve problems that are complex to program, by providing new language layers which should make it easier to express the domain 'knowledge', rules, constraints, etc. to find solutions which are not straight forward to compute.
The "big" win with a language that allows for incremental development is that you (typically) has a read-eval-print loop (or "listener" or "console") that you interact with, plus you tend to not need to lose state when you compile and load new code.
The ability to keep state around from test run to test run means that lengthy computations that are untouched by your changes can simply be kept around instead of being re-computed.
This allows you to experiment and iterate faster. Being able to iterate faster means that exploration is less of a hassle. Very useful for exploratory programming, something that is typical with dealing with less well-defined problems.
When programming a CPU intensive or GPU intensive application on the iPhone or other portable hardware, you have to make wise algorithmic decisions to make your code fast.
But even great algorithm choices can be slow if the language you're using performs more poorly than another.
Is there any hard data comparing Objective-C to C++, specifically on the iPhone but maybe just on the Mac desktop, for performance of various similar language aspects? I am very familiar with this article comparing C and Objective-C, but this is a larger question of comparing two object oriented languages to each other.
For example, is a C++ vtable lookup really faster than an Obj-C message? How much faster? Threading, polymorphism, sorting, etc. Before I go on a quest to build a project with duplicate object models and various test code, I want to know if anybody has already done this and what the results where. This type of testing and comparison is a project in and of itself and can take a considerable amount of time. Maybe this isn't one project, but two and only the outputs can be compared.
I'm looking for hard data, not evangelism. Like many of you I love and hate both languages for various reasons. Furthermore, if there is someone out there actively pursuing this same thing I'd be interesting in pitching in some code to see the end results, and I'm sure others would help out too. My guess is that they both have strengths and weaknesses, my goal is to find out precisely what they are so that they can be avoided/exploited in real-world scenarios.
Mike Ash has some hard numbers for performance of various Objective-C method calls versus C and C++ in his post "Performance Comparisons of Common Operations". Also, this post
by Savoy Software is an interesting read when it comes to tuning the performance of an iPhone application by using Objective-C++.
I tend to prefer the clean, descriptive syntax of Objective-C over Objective-C++, and have not found the language itself to be the source of my performance bottlenecks. I even tend to do things that I know sacrifice a little bit of performance if they make my code much more maintainable.
Yes, well written C++ is considerably faster. If you're writing performance critical programs and your C++ is not as fast as C (or within a few percent), something's wrong. If your ObjC implementation is as fast as C, then something's usually wrong -- i.e. the program is likely a bad example of ObjC OOD because it probably uses some 'dirty' tricks to step below the abstraction layer it is operating within, such as direct ivar accesses.
The Mike Ash 'comparison' is very misleading -- I would never recommend the approach to compare execution times of programs you have written, or recommend it to compare C vs C++ vs ObjC. The results presented are provided from a test with compiler optimizations disabled. A program compiled with optimizations disabled is rarely relevant when you are measuring execution times. To view it as a benchmark which compares C++ against Objective-C is flawed. The test also compares individual features, rather than entire, real world optimized implementations -- individual features are combined in very different ways with both languages. This is far from a realistic performance benchmark for optimized implementations. Examples: With optimizations enabled, IMP cache is as slow as virtual function calls. Static dispatch (as opposed to dynamic dispatch, e.g. using virtual) and calls to known C++ types (where dynamic dispatch may be bypassed) may be optimized aggressively. This process is called devirtualization, and when it is used, a member function which is declared virtual may even be inlined. In the case of the Mike Ash test where many calls are made to member functions which have been declared virtual and have empty bodies: these calls are optimized away entirely when the type is known because the compiler sees the implementation and is able to determine dynamic dispatch is unnecessary. The compiler can also eliminate calls to malloc in optimized builds (favoring stack storage). So, enabling compiler optimizations in any of C, C++, or Objective-C can produce dramatic differences in execution times.
That's not to say the presented results are entirely useless. You could get some useful information about external APIs if you want to determine if there are measurable differences between the times they spend in pthread_create or +[NSObject alloc] on one platform or architecture versus another. Of course, these two examples will be using optimized implementations in your test (unless you happen to be developing them). But for comparing one language to another in programs you compile… the presented results are useless with optimizations disabled.
Object Creation
Consider also object creation in ObjC - every object is allocated dynamically (e.g. on the heap). With C++, objects may be created on the stack (e.g. approximately as fast as creating a C struct and calling a simple function in many cases), on the heap, or as elements of abstract data types. Each time you allocate and free (e.g. via malloc/free), you may introduce a lock. When you create a C struct or C++ object on the stack, no lock is required (although interior members may use heap allocations) and it often costs just a few instructions or a few instructions plus a function call.
As well, ObjC objects are reference counted instances. The actual need for an object to be a std::shared_ptr in performance critical C++ is very rare. It's not necessary or desirable in C++ to make every instance a shared, reference counted instance. You have much more control over ownership and lifetime with C++.
Arrays and Collections
Arrays and many collections in C and C++ also use strongly typed containers and contiguous memory. Since the address of the next element's members are often known, the optimizer can do much more, and you have great cache and memory locality. With ObjC, that's far from reality for standard objects (e.g. NSObject).
Dispatch
Regarding methods, many C++ implementations use few virtual/dynamic calls, particularly in highly optimized programs. These are static method calls and fodder for the optimizers.
With ObjC methods, each method call (objc message send) is dynamic, and is consequently a firewall for the optimizer. Ultimately, that results in many restrictions or inconveniences regarding what you can and cannot do to keep performance at a minimum when writing performance critical ObjC. This may result in larger methods, IMP caching, frequent use of C.
Some realtime applications cannot use any ObjC messaging in their render paths. None -- audio rendering is a good example of this. ObjC dispatch is simply not designed for realtime purposes; Allocations and locks may happen behind the scenes when messaging objects, making the complexity/time of objc messaging unpredictable enough that the audio rendering may miss its deadline.
Other Features
C++ also provides generics/template implementations for many of its libraries. These optimize very well. They are typesafe, and a lot of inlining and optimizations may be made with templates (consider it polymorphism, optimization, and specialization which takes place at compilation). C++ adds several features which just are not available or comparable in strict ObjC. Trying to directly compare langs, objects, and libraries which are very different is not so useful -- it's a very small subset of actual realizations. It's better to expand the question to a library/framework or real program, considering many aspects of design and implementation.
Other Points
C and C++ symbols can be more easily removed and optimized away in various stages of the build (stripping, dead code elimination, inlining and early inlining, as well as Link Time Optimization). The benefits of this include reduced binary sizes, reduced launch/load times, reduced memory consumption, etc.. For a single app, that may not be such a big deal; but if you reuse a lot of code, and you should, then your shared libraries could add a lot of unnecessary weight to the program, if implemented ObjC -- unless you are prepared to jump through some flaming hoops. So scalability and reuse are also factors in medium/large projects, and groups where reuse is high.
Included Libraries
ObjC library implementors also optimize for the environment, so its library implementors can make use of some language and environment features to offer optimized implementations. Although there are some pretty significant restrictions when writing an optimized program in pure ObjC, some highly optimized implementations exist in Cocoa. This is one of Cocoa's strong points, although the C++ standard library (what some people call the STL) is no slouch either. Cocoa operates at a much higher level of abstraction than C++ -- if you don't know well what you're doing (or should be doing), operating closer to the metal can really cost you. Falling back on to a good library implementation if you are not an expert in some domain is a good thing, unless you are really prepared to learn. As well, Cocoa's environments are limited; you can find implementations/optimizations which make better use of the OS.
If you're writing optimized programs and have experience doing so in both C++ and ObjC, clean C++ implementations will often be twice as fast or faster than clean ObjC (yes, you can compare against Cocoa). If you know how to optimize, you can often do better than higher level, general purpose abstractions. Although, some optimized C++ implementations will be as fast as or slower than Cocoa's (e.g. my initial attempt at file I/O was slower than Cocoa's -- primarily because the C++ implementation initializes its memory).
A lot of it comes down to the language features you are familiar with. I use both langs, they both have different strengths and models/patterns. They complement each other quite well, and there are great libraries for both. If you're implementing a complex, performance critical program, correct use of C++'s features and libraries will give you much more control and provide significant advantages for optimization, such that in the right hands, "several times faster" is a good default expectation (don't expect to win every time, or without some work, however). Remember, it takes years to understand C++ well enough to really reach that point.
I keep the majority of my performance critical paths as C++, but also recognize that ObjC is also a very good solution for some problems, and that there are some very good libraries available.
It's very hard to collect "hard data" for this that's not misguiding.
The biggest problem with doing a feature-to-feature comparison like you suggest is that the two languages encourage very different coding styles. Objective-C is a dynamic language with duck typing, where typical C++ usage is static. The same object-oriented architecture problem would likely have very different ideal solutions using C++ or Objective-C.
My feeling (as I have programmed much in both languages, mostly on huge projects): To maximize Objective-C performance, it has to be written very close to C. Whereas with C++, it's possible to make much more use of the language without any performance penalty compared to C.
Which one is better? I don't know. For pure performance, C++ will always have the edge. But the OOP style of Objective-C definitely has its merits. I definitely think it is easier to keep a sane architecture with it.
This really isn't something that can be answered in general as it really depends on how you use the language features. Both languages will have things that they are fast at, things that they are slow at, and things that are sometimes fast and sometimes slow. It really depends on what you use and how you use it. The only way to be certain is to profile your code.
In Objective C you can also write c++ code, so it might be easier to code in Objective C for the most part, and if you find something that doesn't perform well in it, then you can have a go at writting a c++ version of it and seeing if that helps (C++ tends to optimize better at compile time). Objective C will be easier to use if APIs you are interfacing with are also written in it, plus you might find it's style of OOP is easier or more flexible.
In the end, you should go with what you know you can write safe, robust code in and if you find an area that needs special attention from the other language, then you can swap to that. X-Code does allow you to compile both in the same project.
I have a couple of tests I did on an iPhone 3G almost 2 years ago, there was no documentation or hard numbers around in those days. Not sure how valid they still are but the source code is posted and attached.
This isn't a very extensive test, I was mainly interested in NSArray vs C Array for iterating a large number of objects.
http://memo.tv/nsarray_vs_c_array_performance_comparison
http://memo.tv/nsarray_vs_c_array_performance_comparison_part_ii_makeobjectsperformselector
You can see the C Array is much faster at high iterations. Since then I've realized that the bottleneck is probably not the iteration of the NSArray but the sending of the message. I wanted to try methodForSelector and calling the methods directly to see how big the difference would be but never got round to it. According to Mike Ash's benchmarks it's just over 5x faster.
I don't have hard data for Objective C, but I do have a good place to look for C++.
C++ started as C with Classes according to Bjarne Stroustroup in his reflection on the early years of C++ (http://www2.research.att.com/~bs/hopl2.pdf), so C++ can be thought of (like Objective C) as pushing C to its limits for object orientation.
What are those limits? In the 1994-1997 time frame, a lot of researchers figured out that object-orientation came at a cost due to dynamic binding, e.g. when C++ functions are marked virtual and there may/may not be children classes that override these functions. (In Java and C#, all functions expect ctors are inherently virtual, and there isnt' much you can do about it.) In "A Study of Devirtualization Techniques for a Java Just-In-Time Compiler" from researchers at IBM Research Tokyo, they contrast the techniques used to deal with this, including one from Urz Hölzle and Gerald Aigner. Urz Hölzle, in a separate paper with Karel Driesen, had shown that on average 5.7% of time in C++ programs (and up to ~50%) was spent in calling virtual functions (e.g. vtables + thunks). He later worked with some Smalltalk researachers in what ended up the Java HotSpot VM to solve these problems in OO. Some of these features are being backported to C++ (e.g. 'protected' and Exception handling).
As I mentioned, C++ is static typed where Objective C is duck typed. The performance difference in execution (but not lines of code) probably is a result of this difference.
This study says to really get the performance in a CPU intensive game, you have to use C. The linked article is complete with a XCode project that you can run.
I believe the bottom line is: Use Objective-C where you must interact with the iPhone's functions (after all, putting trampolines everywhere can't be good for anyone), but when it comes to loops, things like vector object classes, or intensive array access, stick with C++ STL or C arrays to get good performance.
I mean it would be totally silly to see position = [[Vector3 alloc] init] ;. You're just asking for a performance hit if you use references counts on basic objects like a position vector.
yes. c++ reign supreme in performance/expresiveness/resource tradeoff.
"I'm looking for hard data, not evangelism". google is your best friend.
obj-c nsstring is swapped with c++'s by apple enginneers for performance. in a resource constrained devices, only c++ cuts it as a MAINSTREAM oop language.
NSString stringWithFormat is slow
obj-c oop abstraction is deconstructed into procedural-based c-structs for performance, otherwise a MAGNITUDE order slower than java! the author is also aware of message caching - yet no-go. so modeling lots of small players/enemies objects is done in oop with c++ or else, lots of Procedural structs with a simple OOP wrapper around it with obj-c. there can be one paradigm that equates Procedural + Object-Oriented Programming = obj-c.
http://ejourneyman.wordpress.com/2008/04/23/writing-a-ray-tracer-for-cocoa-objective-c/
With the growth of dynamically typed languages, as they give us more flexibility, there is the very likely probability that people will write programs that go beyond what the specification allows.
My thinking was influenced by this question, when I read the answer by bobince:
A question about JavaScript's slice and splice methods
The basic thought is that splice, in Javascript, is specified to be used in only certain situations, but, it can be used in others, and there is nothing that the language can do to stop it, as the language is designed to be extremely flexible.
Unless someone reads through the specification, and decides to adhere to it, I am fairly certain that there are many such violations occuring.
Is this a problem, or a natural extension of writing such flexible languages? Or should we expect tools like JSLint to help be the specification police?
I liked one answer in this question, that the implementation of python is the specification. I am curious if that is actually closer to the truth for these types of languages, that basically, if the language allows you to do something then it is in the specification.
Is there a Python language specification?
UPDATE:
After reading a couple of comments, I thought I would check the splice method in the spec and this is what I found, at the bottom of pg 104, http://www.mozilla.org/js/language/E262-3.pdf, so it appears that I can use splice on the array of children without violating the spec. I just don't want people to get bogged down in my example, but hopefully to consider the question.
The splice function is intentionally generic; it does not require that its this value be an Array object.
Therefore it can be transferred to other kinds of objects for use as a method. Whether the splice function
can be applied successfully to a host object is implementation-dependent.
UPDATE 2:
I am not interested in this being about javascript, but language flexibility and specs. For example, I expect that the Java spec specifies you can't put code into an interface, but using AspectJ I do that frequently. This is probably a violation, but the writers didn't predict AOP and the tool was flexible enough to be bent for this use, just as the JVM is also flexible enough for Scala and Clojure.
Whether a language is statically or dynamically typed is really a tiny part of the issue here: a statically typed one may make it marginally easier for code to enforce its specs, but marginally is the key word here. Only "design by contract" -- a language letting you explicitly state preconditions, postconditions and invariants, and enforcing them -- can help ward you against users of your libraries empirically discovering what exactly the library will let them get away with, and taking advantage of those discoveries to go beyond your design intentions (possibly constraining your future freedom in changing the design or its implementation). And "design by contract" is not supported in mainstream languages -- Eiffel is the closest to that, and few would call it "mainstream" nowadays -- presumably because its costs (mostly, inevitably, at runtime) don't appear to be justified by its advantages. "Argument x must be a prime number", "method A must have been previously called before method B can be called", "method C cannot be called any more once method D has been called", and so on -- the typical kinds of constraints you'd like to state (and have enforced implicitly, without having to spend substantial programming time and energy checking for them yourself) just don't lend themselves well to be framed in the context of what little a statically typed language's compiler can enforce.
I think that this sort of flexibility is an advantage as long as your methods are designed around well defined interfaces rather than some artificial external "type" metadata. Most of the array functions only expect an object with a length property. The fact that they can all be applied generically to lots of different kinds of objects is a boon for code reuse.
The goal of any high level language design should be to reduce the amount of code that needs to be written in order to get stuff done- without harming readability too much. The more code that has to be written, the more bugs get introduced. Restrictive type systems can be, (if not well designed), a pervasive lie at worst, a premature optimisation at best. I don't think overly restrictive type systems aid in writing correct programs. The reason being that the type is merely an assertion, not necessarily based on evidence.
By contrast, the array methods examine their input values to determine whether they have what they need to perform their function. This is duck typing, and I believe that this is more scientific and "correct", and it results in more reusable code, which is what you want. You don't want a method rejecting your inputs because they don't have their papers in order. That's communism.
I do not think your question really has much to do with dynamic vs. static typing. Really, I can see two cases: on one hand, there are things like Duff's device that martin clayton mentioned; that usage is extremely surprising the first time you see it, but it is explicitly allowed by the semantics of the language. If there is a standard, that kind of idiom may appear in later editions of the standard as a specific example. There is nothing wrong with these; in fact, they can (unless overused) be a great productivity boost.
The other case is that of programming to the implementation. Such a case would be an actual abuse, coming from either ignorance of a standard, or lack of a standard, or having a single implementation, or multiple implementations that have varying semantics. The problem is that code written in this way is at best non-portable between implementations and at worst limits the future development of the language, for fear that adding an optimization or feature would break a major application.
It seems to me that the original question is a bit of a non-sequitor. If the specification explicitly allows a particular behavior (as MUST, MAY, SHALL or SHOULD) then anything compiler/interpreter that allows/implements the behavior is, by definition, compliant with the language. This would seem to be the situation proposed by the OP in the comments section - the JavaScript specification supposedly* says that the function in question MAY be used in different situations, and thus it is explicitly allowed.
If, on the other hand, a compiler/interpreter implements or allows behavior that is expressly forbidden by a specification, then the compiler/interpreter is, by definition, operating outside the specification.
There is yet a third scenario, and an associated, well defined, term for those situations where the specification does not define a behavior: undefined. If the specification does not actually specify a behavior given a particular situation, then the behavior is undefined, and may be handled either intentionally or unintentionally by the compiler/interpreter. It is then the responsibility of the developer to realize that the behavior is not part of the specification, and, should s/he choose to leverage the behavior, the developer's application is thereby dependent upon the particular implementation. The interpreter/compiler providing that implementation is under no obligation to maintain the officially undefined behavior beyond backwards compatibility and whatever commitments the producer may make. Furthermore, a later iteration of the language specification may define the previously undefined behavior, making the compiler/interpreter either (a) non-compliant with the new iteration, or (b) come out with a new patch/version to become compliant, thereby breaking older versions.
* "supposedly" because I have not seen the spec, myself. I go by the statements made, above.