fmi_adapter looks like an awesome way to use an FMU as a ROS node. However, I don't see anything about the opposite/inverse problem - generating an FMU from a ROS node. Is there a reason that this is not possible in general? Or is it just an unusual pattern that no one has ever written a library for because it would be seldom used?
I'm the developer of the fmi_adapter package but, admitted, never thought about the opposite direction. The big difference is that with an FMU you have an explicit specification of the variables (i.e., inputs and outputs), whereas with ROS these would have to be analyzed from the code (or can even be determined at runtime only). This would make a corresponding generator significantly more complex.
Related
We have huge code base and we are generating issues that would have been caught at compile time in type languages such as Java but we are not catching them until runtime in Ruby. This is bad since we generate bugs that most of the time are typos or refactoring that leaves some invalid code.
Example:
def mysuperfunc
# some code goes here
# this was a valid call but not anymore since enforcesecurity
# signature changed
#system.enforcesecurity
end
I mean, IDEs can do it but some guys use ATOM or sublime, so we need something to "compile" and report that kind of issues so they don't reach deployment. What have you been using?
This is generating a little percentage of our bug reports, but since we are forced to produce at a ridiculous pace we don't have 100% code coverage. If there is no tool to help, I'll just make sure everybody uses and IDE and run the reports with tools such as Rubymine.
Our stack includes, rspec, minitest, SimpleCov. We enforce code reviews, multistack deployments (dev, qa, pre-prod, sandbox, prod). And still some issues are reaching higher level and makes us programmers look bad. I'm not looking of magic, just a little automation that might help a bit.
Unfortunately, the Halting Problem, Rice's Theorem, and all the other Undecidability and Uncomputability Results tell us that it is simply impossible in the general case to statically determine any "interesting" property about the runtime behavior of a program. We cannot even statically determine something as simple as "will it halt", so how are we going to determine "is bug-free"?
There are certain things that can be statically determined, and there are certain restricted programs for which some interesting properties can be statically determined, but largely, this is not possible. And even to the small extent that it is possible, it generally requires the language to be specifically designed to be easy to statically analyze (which Ruby isn't).
That being said, there are certain tools that contain certain heuristics to point out code that may have problems. There are certain coding standards that may help avoid bugs, and there are tools to enforce those coding standards. Keywords to search for are "code quality tools", "linter", "static analyzer", etc. You have already been given examples in the other answers and comments, and given those examples and these keywords, you'll likely find more.
However, I also wanted to discuss something you wrote:
we are forced to produce at a ridiculous pace we don't have 100% code coverage
That's a problem, which has to be approached from two sides:
Practice, practice, practice. You need to practice testing and writing high-quality code until it is so naturally to you that not doing it actually ends up being harder and slower. It should become second nature to you, such that under pressure when your mind goes blank, the only thing you know is to write tests and write well-designed, well-factored, high-quality code. Note: I'm talking about deliberate practice, which means setting time aside to really practice … and practice is practice, it's not work, it's not fun, it's not hobby, if you don't delete the code you wrote immediately after you have written it, you are not practicing, you are working.
Sustainable Pace. You should never develop faster than the pace you could sustain indefinitely while still producing well-tested, well-designed, well-factored, high-quality code, having a fulfilling social life, no stress, plenty of free time, etc. This is something that has to be backed and supported and understood by management.
I'm unaware of anything exactly like you want. However, there are a few gems that will analyze code and warn you about some errors and/or bad practices. Try these:
https://github.com/bbatsov/rubocop
https://github.com/railsbp/rails_best_practices
FLAY
https://rubygems.org/gems/flay
Via the repo https://github.com/seattlerb/flay:
DESCRIPTION:
Flay analyzes code for structural similarities. Differences in literal
values, variable, class, method names, whitespace, programming style,
braces vs do/end, etc are all ignored. Making this totally rad.
[FEATURES:]
Reports differences at any level of code.
Adds a score multiplier to identical nodes.
Differences in literal values, variable, class, and method names are ignored.
Differences in whitespace, programming style, braces vs do/end, etc are ignored.
Works across files.
Add the flay-persistent plugin to work across large/many projects.
Run --diff to see an N-way diff of the code.
Provides conservative (default) and --liberal pruning options.
Provides --fuzzy duplication detection.
Language independent: Plugin system allows other languages to be flayed.
Ships with .rb and .erb.
javascript and others will be
available separately.
Includes FlayTask for Rakefiles.
Uses path_expander, so you can use:
dir_arg -- expand a directory automatically
#file_of_args -- persist arguments in a file
-path_to_subtract -- ignore intersecting subsets of
files/directories
Skips files matched via patterns in .flayignore (subset format of .gitignore).
Totally rad.
FLOG
https://rubygems.org/gems/flog
Via the repo https://github.com/seattlerb/flog:
DESCRIPTION:
Flog reports the most tortured code in an easy to read pain report.
The higher the score, the more pain the code is in.
[FEATURES:]
Easy to read reporting of complexity/pain.
Uses path_expander, so you can use:
dir_arg – expand a directory automatically
#file_of_args – persist arguments in a file
-path_to_subtract – ignore intersecting subsets of files/directories
SYNOPSIS:
% ./bin/flog -g lib
Total Flog = 1097.2 (17.4 flog / method)
323.8: Flog total
85.3: Flog#output_details
61.9: Flog#process_iter
53.7: Flog#parse_options
...
There is a ruby gem called guard that does automated testing. You can set your own custom rules.
For example, you can make it where anytime you modify certain files, the test framework will automatically run.
Here is the link for guard
I am new to Rascal and I am looking forward to construct Control Flow Graph for java. How to make use of DCFlow to construct it?
This is something I've started on but hasn't been completed yet (mainly due to a lack of time, most of my work is on PHP program analysis). Once this is fully defined I'll post it on GitHub. My goal is to build it over the M3 definition of Java since we already have the extraction code in place to generate M3 models, and these optionally include ASTs (which we need for CFG generation).
I'm taking a compiler-design class where we have to implement our own compiler (using flex and bison). I have had experience in parsing (writing EBNF's and recursive-descent parsers), but this is my first time writing a compiler.
The language design is pretty open-ended (the professor has left it up to us). In class, the professor went over generating intermediate code. He said that it is not necessary for us to construct an Abstract Syntax Tree or a parse tree while parsing, and that we can generate the intermediate code as we go.
I found this confusing for two reasons:
What if you are calling a function before it is defined? How can you resolve the branch target? I guess you would have to make it a rule that you have to define functions before you use them, or maybe pre-define them (like C does?)
How would you deal with conditionals? If you have an if-else or even just an if, how can you resolve the branch target for the if when the condition is false (if you're generating code as you go)?
I planned on generating an AST and then walking the tree after I create it, to resolve the addresses of functions and branch targets. Is this correct or am I missing something?
The general solution to both of your issues is to keep a list of addresses that need to be "patched." You generate the code and leave holes for the missing addresses or offsets. At the end of the compilation unit, you go through the list of holes and fill them in.
In FORTH the "list" of patches is kept on the control stack and is unwound as each control structure terminates. See FORTH Dimensions
Anecdote: an early Lisp compiler (I believe it was Lisp) generated a list of machine code instructions in symbolic format with forward references to the list of machine code for each branch of a conditional. Then it generated the binary code walking the list backwards. This way the code location for all forward branches was known when the branch instruction needed to be emitted.
The Crenshaw tutorial is a concrete example of not using an AST of any kind. It builds a working compiler (including conditionals, obviously) with immediate code generation targeting m68k assembly.
You can read through the document in an afternoon, and it is worth it.
I have existing java code and need to create Design Document based on that.
For starter even if I could get all functions with input / output parameters that will help in overall proces.
Note: There is not commeted documentation on any procedures, function or classes.
Last but not least. Let me know for any good tool which will reduce time required for this phase. As currently we write every flow and related stuffs.
What you want is just too much. Quoting Linus Torvalds: “Good code is its own best documentation.”. Anyway, I digress.
You might want to look into UML tools which generate class/sequence diagrams from the code. There are many of them but only a handful support reverse engineering (into and from the class diagram), and even fewer subset support the same to/from sequence diagram. I only know MagicDraw could do this, but I am biased as I used to work for the manufacturer of this tool so do your shopping around first.
Use java docs: http://www.oracle.com/technetwork/java/javase/documentation/index-137868.html
or Introspection: http://docs.oracle.com/javase/tutorial/reflect/class/classMembers.html
I am not asking the static code analysis which is provided by StyleCop or Fxcop. Both are having different purpose and it serves well. I am asking whether is there a way to find the code coverage of your user control or sub module? For ex, you have an application which uses the helper classes in a separate assembly. Inorder to ensure the unit testing code coverage, we need to run the application and ensure using NCover or similar tool.
My requirement is, without running it, is there any possible to find code coverage of the helper classes or similar kind of assemblies?
See Static Estimation for Test Coverage for a technique that estimates coverage without executing the source code.
The basic idea is to compute a program slice for each test case, and then "count" what the slice enumerates. A (forward) slice is effectively that part of a program that you can reach from a specific starting point in the code, in this case, the test code.
While the technical paper above is hard to get if you're not an ACM member [or you didn't attend the conference where it was presented :], there's a slide presentation here.
Of course, running this static estimator only tells you (roughly) what code will be exercised. It doesn't substitute for actually running the tests, and verifying that they pass!
In general, the answer is no. This is equivalent to the halting problem, which is not computable.
There are (research) tools based on abstract interpretation or model checking that can show coverage properties without execution, for subsets of language. See, e.g.
"Analyzing Functional Coverage in Bounded Model Checking", Grosse, D. Kuhne, U. Drechsler, R. 2008
In general, yes, there are approaches, but they're specialized, and may require some formal methods experience. This kind of stuff is still cutting edge research.
I would say no; with the exception of 'dead code' which a compiler can determine.
My definition of code coverage is a result which indicates how many times each line of code is run in your program: which, of course, means running the program. The determining factor here is usually the values of data passing through the program which the determine the paths of executions taken by conditionals. A static analysis, like a compiler, could deduce lines of code that cannot run under any conditions.
An example here is if your program uses a third-party library, but there is a bug in the library. If your program never uses those parts of the library, or the data you send to the library causes it to avoid the bug, then you won't be affected.
You could write a program that, by reflection, assumes that all conditionals will be taken, and follows all function calls, through all derived classes, but I'm not sure what this will tell you. It certainly can't tell you whether or not there are any bugs in the lines of code covered.
Coverity Static Analysis is a tool that is can identify many secuirty flaws in a program. It can also identify dead code and can be used to help satisfy testing regulations such as D0178B which requires that the developers demonstrate that all code can be executed.
If you are using Visual Studio, you can first run 'Analyze Code Coverage', Then you can export code Coverage results using below Button(marked in Green) in Visual Studio:
Later you can import the Coverage Result file back to Visual Studio