I write a project for a non POSIX embedded system so I cannot use gcc option --coverage (i don't have read or write). What else can I do to produce gcov like output. I do have an output function.
It can be most easily done with by a processor with embedded trace, a board design that exposes the trace port, and a suitable hardware debugger and associate software. For example, many Cortex-M based devices include ARM's embedded trace macrocell (ETM), and this is supported by Keil's uVision IDE and ULINK-Pro debugger to provide code coverage and instruction/source level trace as well as real-time profiling. Hardware trace has the advantage that it is non-intrusive - the code runs in real-time.
If you do not have the hardware support, you may have to resort to simulation. Many tool-chains include an instruction level simulator that will perform trace, code-coverage, and profiling, but you may have to create debug scripts or code stubs to simulate hardware to coerce the execution of all paths.
A third alternative is to build the code on a desktop platform with stubs to replace target hardware dependencies, and perform testing and code coverage on that. You have to trust that the target C compiler and the test system compiler both translate the source with identical semantics. The advantage here is that the debug tools available are often superior to those available to embedded systems. You can also test much of your code before any hardware is available, and in most cases execute code much faster, possibly allowing more extensive testing.
Not having a POSIX API does not preclude using GCC, it merely precludes using the GNU C library. On embedded systems without POSIX, alternative C libraries are used such as Newlib. Newlib has a system porting layer where I/O and basic heap management are implemented.
Disclaimer: The company (Rapita Systems) I work for provides a code coverage solution aimed at embedded applications.
Because embedded systems bring their own, special and widely varying requirements, the "best" solution for code coverage also varies widely.
Where you have trace-based devices, like ARM chips with ETM or NEXUS-enabled parts, you can perform coverage without instrumentation via debuggers.
Otherwise, you are most likely faced with an instrumentation-based solution:
For RAM-limited solutions, a good solution is to write instrumentation to an I/O port
Alternatively, you can record instrumentation to a RAM buffer, and use a wide variety of means to extract this from the target.
Of course lots of different flavours of code coverage are also available: function, statement, decision/branch, MC/DC
Our family of C/C++ test coverage tools instrument the source code, producing a program you compile with you embedded compiler, that will collect test coverage data into a "small" data structure added to the program. This works with various dialects including ANSI, GCC, Microsoft and GreenHills.
You have to export that data structure from the embedded execution context to a file on a PC; this is often easy to do with a spare serial or parallel port and a small bit of custom code specific to your port. The tools will provide test coverage views and summaries with that resulting files.
So, you can use these tools to collect test coverage data from your embedded system, in most practical circumstances.
If your embedded target is supported by GCC-based cross-toolchains, you may find my blog post useful.
The main idea is that you compile your code with the appropriate gcov options, and then create the coverage information in memory (what in the end is stored in .gcda files). You can then place appropriate breakpoints with your GDB, and dump this information over your debug link (serial, JTAG, whatever).
Have a look at my blog post - I describe things in great detail.
I'm thinking about writing my own little language.
I found a few options, but feel free to suggest more.
JVM
Parrot
OSA
A lot of languages are using the JVM, but unless you write a Java-ish language, all the power the stdlib gives you is going to feel ugly; It's not very good at dynamic stuff either.
Parrot seems a good VM for developing languages, but it has a little abandoned/unfinished/hobby project smell to it.
OSA is what powers Applescript, not a particularly well known VM, but I use Mac, and it offers good system integration.
CLR+Mac doesn't seem a good combination...
My language is going to be an object orientated functional concurrent dataflow language with strong typing and a mix of Python and Lisp syntax.
Sounds good, eh?
[edit]
I accepted Python for now, but I'd like to hear more about OSA and Parrot.
One approach I've played with is to use the Python ast module to build an abstract syntax tree representing the code to run. The Python compile function can compile an AST into Python bytecode, which exec can then run. This is a bit higher level than directly generating bytecode, but you will have to deal with some quirks of the Python language (for example, the fundamental difference between statements and expressions).
In doing this I've also written a "deparse" module that attempts to convert an AST back to equivalent Python source code, just for debugging. You can find code in the psil repository if you're interested.
Have a look at LLVM. It's not a pure VM as such, more a framework with it's own IR that allows you to build high level VMs. Has nice stuff like static code analysis and JIT support
Lua has a small, well-written and fast VM
Python VM - you can really attach a new language to it if you want. Or write (use?) something like tinypy which is a small and simple implementation of the Python VM.
Both options above have access to useful standard libraries that will save you work, and are coded in relatively clean and modular C, so they shouldn't be hard to connect to.
That said, I disagree that Parrot is abandoned/hobby. It's quite mature, and has some very strong developers working on it. Furthermore, it's specifically a VM designed to be targeted by multiple dynamic languages. Thus, is was designed with flexibility in mind.
Have you considered Pypy? From what I've read, in addition to being a Python JIT Compiler, it also has the capability to handle other languages. For example there is a tutorial which explains how to create a Brainfuck JIT compiler using Pypy.
I see here that there are a load of languages aside from Java that run on the JVM. I'm a bit confused about the whole concept of other languages running in the JVM. So:
What is the advantage in having other languages for the JVM?
What is required (in high level terms) to write a language/compiler for the JVM?
How do you write/compile/run code in a language (other than Java) in the JVM?
EDIT: There were 3 follow up questions (originally comments) that were answered in the accepted answer. They are reprinted here for legibility:
How would an app written in, say, JPython, interact with a Java app?
Also, Can that JPython application use any of the JDK functions/objects??
What if it was Jaskell code, would the fact that it is a functional language not make it incompatible with the JDK?
To address your three questions separately:
What is the advantage in having other languages for the JVM?
There are two factors here. (1) Why have a language other than Java for the JVM, and (2) why have another language run on the JVM, instead of a different runtime?
Other languages can satisfy other needs. For example, Java has no built-in support for closures, a feature that is often very useful.
A language that runs on the JVM is bytecode compatible with any other language that runs on the JVM, meaning that code written in one language can interact with a library written in another language.
What is required (in high level terms) to write a language/compiler for the JVM?
The JVM reads bytecode (.class) files to obtain the instructions it needs to perform. Thus any language that is to be run on the JVM needs to be compiled to bytecode adhering to the Sun specification. This process is similar to compiling to native code, except that instead of compiling to instructions understood by the CPU, the code is compiled to instructions that are interpreted by the JVM.
How do you write/compile/run code in a language (other than Java) in the JVM?
Very much in the same way you write/compile/run code in Java. To get your feet wet, I'd recommend looking at Scala, which runs flawlessly on the JVM.
Answering your follow up questions:
How would an app written in, say, JPython, interact with a Java app?
This depends on the implementation's choice of bridging the language gap. In your example, Jython project has a straightforward means of doing this (see here):
from java.net import URL
u = URL('http://jython.org')
Also, can that JPython application use any of the JDK functions/objects?
Yes, see above.
What if it was Jaskell code, would the fact that it is a functional language not make it incompatible with the JDK?
No. Scala (link above) for example implements functional features while maintaining compatibility with Java. For example:
object Timer {
def oncePerSecond(callback: () => unit) {
while (true) { callback(); Thread sleep 1000 }
}
def timeFlies() {
println("time flies like an arrow...")
}
def main(args: Array[String]) {
oncePerSecond(timeFlies)
}
}
You need other languages on the JVM for the same reason you need multiple programming languages in general: Different languages are better as solving different problems ... static typing vs. dynamic typing, strict vs. lazy ... Declarative, Imperative, Object Oriented ... etc.
In general, writing a "compiler" for another language to run on the JVM (or on the .Net CLR) is essentially a matter of compiling that language into java bytecode (or in the case of .Net, IL) instead of to assembly/machine language.
That said, a lot of the extra languages that are being written for JVM aren't compiled, but rather interpreted scripting languages...
Turning this on its head, consider you want to design a new language and you want it to run in a managed runtime with a JIT and GC. Then consider that you could:
(a) write you own managed runtime (VM) and tackle all sorts of technically difficult issues that will doubtless lead to many bugs, bad performance, improper threading and a great deal of portability effort
or
(b) compile your language into bytecode that can run on the Java VM which is already quite mature, fast and supported on a number of platforms (sometimes with more than one choice of vendor impementation).
Given that the JavaVM bytecode is not tied so closely to the Java language as to unduly restrict the type of language you can implement, it has been a popular target environment for languages that want to run in a VM.
Java is a fairly verbose programming language that is getting outdated very quickly with all of the new fancy languages/frameworks coming out in the past 5 years. To support all the fancy syntax that people want in a language AND preserve backwards compatibility it makes more sense to add more languages to the runtime.
Another benefit is it lets you run some web frameworks written in Ruby ala JRuby (aka Rails), or Grails(Groovy on Railys essentially), etc. on a proven hosting platform that likely already is in production at many companies, rather than having to using that not nearly as tried and tested Ruby hosting environments.
To compile the other languages you are just converting to Java byte code.
I would answer, “because Java sucks” but then again, perhaps that's too obvious … ;-)
The advantage to having other languages for the JVM is quite the same as the advantage to having other languages for computer in general: while all turing-complete languages can technically accomplish the same tasks, some languages make some tasks easier than others while other languages make other tasks easier. Since the JVM is something we already have the ability to run on all (well, nearly all) computers, and a lot of computers, in fact already have it, we can get the "write once, run anywhere" benefit, but without requiring that one uses Java.
Writing a language/compiler for the JVM isn't really different from writing one for a real machine. The real difference is that you have to compile to the JVM's bytecode instead of to the machine's executable code, but that's really a minor difference in the grand scheme of things.
Writing code for a language other than Java in the JVM really isn't different from writing Java except, of course, that you'll be using a different language. You'll compile using the compiler that somebody writes for it (again, not much different from a C compiler, fundamentally, and pretty much not different at all from a Java compiler), and you'll end up being able to run it just like you would compiled Java code since once it's in bytecode, the JVM can't tell what language it came from.
Different languages are tailored to different tasks. While certain problem domains fit the Java language perfectly, some are much easier to express in alternative languages. Also, for a user accustomed to Ruby, Python, etc, the ability to generate Java bytecode and take advantage of the JDK classes and JIT compiler has obvious benefits.
Answering just your second question:
The JVM is just an abstract machine and execution model. So targetting it with a compiler is just the same as any other machine and execution model that a compiler might target, be it implemented in hardware (x86, CELL, etc) or software (parrot, .NET). The JVM is fairly simple, so its actually a fairly easy target for compilers. Also, implementations tend to have pretty good JIT compilers (to deal with the lousy code that javac produces), so you can get good performance without having to worry about a lot of optimizations.
A couple of caveats apply. First, the JVM directly embodies java's module and inheritance system, so trying to do anything else (multiple inheritance, multiple dispatch) is likely to be tricky and require convoluted code. Second, JVMs are optimized to deal with the kind of bytecode that javac produces. Producing bytecode that is very different from this is likely to get into odd corners of the JIT compiler/JVM which will likely be inefficient at best (at worst, they can crash the JVM or at least give spurious VirtualMachineError exceptions).
What the JVM can do is defined by the JVM's bytecode (what you find in .class files) rather than the source language. So changing the high level source code language isn't going to have a substantial impact on the available functionality.
As for what is required to write a compiler for the JVM, all you really need to do is generate correct bytecode / .class files. How you write/compile code with an alternate compiler sort of depends on the compiler in question, but once the compiler outputs .class files, running them is no different than running the .class files generated by javac.
The advantage for these other languages is that they get relatively easy access to lots of java libraries.
The advantage for Java people varies depending on language -- each has a story tell Java coders about what they do better. Some will stress how they can be used to add dynamic scripting to JVM-based apps, others will just talk about how their language is easier to use, has a better syntax, or so forth.
What's required are the same things to write any other language compiler: parsing to an AST, then transforming that to instructions for the target architecture (byte code) and storing it in the right format (.class files).
From the users' perspective, you just write code and run the compiler binaries, and out comes .class files you can mix in with those your java compiler produces.
The .NET languages are more for show than actual usefulness. Each language has been so butchered, that they're all C# with a new face.
There are a variety of reasons to provide alternative languages for the Java VM:
The JVM is multiplatform. Any language ported to the JVM gets that as a free bonus.
There is quite a bit of legacy code out there. Antiquated engines like ColdFusion perform better while offering customers the ability to slowly phase their applications from the legacy solution to the modern solution.
Certain forms of scripting are better suited to rapid development. JavaFX, for example, is designed with rapid Graphical development in mind. In this way it competes with engines like DarkBasic. (Processing is another player in this space.)
Scripting environments can offer control. For example, an application may wish to expose a VBA-like environment to the user without exposing the underlying Java APIs. Using an engine like Rhino can provide an environment that supports quick and dirty coding in a carefully controlled sandbox.
Interpreted scripts mean that there's no need to recompile anything. No need to recompile translates into a more dynamic environment. e.g. Despite OpenOffice's use of Java as a "scripting language", Java sucks for that use. The user has to go through all kinds of recompile/reload gyrations that are unnecessary in a dynamic scripting environment like Javascript.
Which brings me to another point. Scripting engines can be more easily stopped and reloaded without stopping and reloading the entire JVM. This increases the utility of the scripting language as the environment can be reset at any time.
It's much easier for a compiler writer to generate JVM or CLR byte-codes. They are a much cleaner and higher level abstraction than any machine language. Because of this, it is much more feasible to experiment with creating new languages than ever before, because all you have to do is target one of these VM architectures and you will have a set of tools and libraries already available for your language. They let language designers focus more on the language than all the necessary support infrastructure.
Because the JSR process is rendering Java more and more dead: http://www.infoq.com/news/2009/01/java7-updated
It's a shame that even essential and long known additions like Closures are not added just because the members cannot agree on an implementation.
Java has accumulated a massive user base over seven major versions (from 1.0 to 1.6). Its capability to evolve is limited by the need to preserve backwards compatibility for the uncountable millions of lines of Java code running in production.
This is a problem because Java needs to evolve to:
compete with newer programming languages that have learned from Java's successes and failures.
incorporate new advances in programming language design.
allow users to take full advantage of advances in hardware - e.g. multi-core processors.
fix some cutting edge ideas that introduced unexpected problems (e.g. checked exceptions, generics).
The requirement for backwards compatibility is a barrier to staying competitive.
If you compare Java to C#, Java has the advantage in mature, production ready libraries and frameworks, and a disadvantage in terms of language features and rate of increase in market share. This is what you would expect from comparing two successful languages that are one generation apart.
Any new language has the same advantage and disadvantage that C# has compared to Java to an extreme degree. One way of maximizing the advantage in terms of language features, and minimizing the disadvantage in terms of mature libraries and frameworks is to build the language for an existing virtual machine and make it interoperable with code written for that virtual machine. This is the reason behind the modest success of Groovy and Clojure; and the excitement around Scala. Without the JVM these languages could only ever have occupied a tiny niche in a very specialized market segment, whereas with the JVM they occupy a significant niche in the mainstream.
They do it to keep up with .Net. .Net allows C#, VB, J# (formerly), F#, Python, Ruby (coming soon), and c++. I'm probably missing some. Probably the big one in there is Python, for the scripting people.
To an extent it is probably an 'Arms Race' against the .NET CLR.
But I think there are also genuine reasons for introducing new languages to the JVM, particularly when they will be run 'in parallel', you can use the right language for the right job, a scripting language like Groovy may be exactly what you need for your page presentation, whereas regular old Java is better for your business logic.
I'm going to leave someone more qualified to talk about what is required to write a new language/compiler.
As for how to writing code, you do it in notepad/vi as usual! (or use a development tool that supports the language if you want to do it the easy way.) Compiling will require a special compiler for the language that will interpret and compile it into bytecode.
Since java also produces bytecode technically you don't need to do anything special to run it.
The reason is that the JVM platform offers a lot of advantages.
Giant number of libraries
Broader degree of platform
implementations
Mature frameworks
Legacy code that's
already part of your infrastructure
The languages Sun is trying to support with their Scripting spec (e.g. Python, Ruby) are up and comers largely due to their perceived productivity enhancements. Running Jython allows you to, in theory, be more productive, and leverage the capabilities of Python to solve a problem more suited to Python, but still be able to integrate, on a runtime level, with your existing codebase. The classic implementations of Python and Ruby effect the same ability for C libraries.
Additionally, it's often easier to express some things in a dynamic language than in Java. If this is the case, you can go the other way; consume Python/Ruby libraries from Java.
There's a performance hit, but many are willing to accept that in exchange for a less verbose, clearer codebase.
I need to estimate the code coverage of a test set.
The tests are run on a J2ME application, on a physical device.
MIDP 2.1, CLDC 1.1 and JSR-75 FileConnection are available.
As J2ME is (roughly) a subset of J2SE, tools using java.io.File (like those listed in the only answer so far..) can not be used.
This is mainly to identify pieces of code the tests do not touch at all.
It would also be nice to be able to combine the report data arbitrarily afterwards, so I can see how much a new test actually increases coverage.
Are there any alternatives to Cobertura4j2me?
There's lots of Java code coverage tools. Many of them work by using JVM features not available in embedded systems due to space limitations.
One that uses only an additional boolean array in which to hold the coverage data can be found at
http://www.semanticdesigns.com/Products/TestCoverage/JavaTestCoverage.html
You have to code an additional routine that dumps that array out of your embedded device into a file on a PC, but that's generally a pretty easy task (e.g., several hours work, once).
Here's a slew of alternatives.
http://java-source.net/open-source/code-coverage