In Paper [A Software Product Line for Static Analyses(2014)], there is an illustration related constructing call graph(Listing7).
In this example, Line14 is related to construct call graph. while i check the src code and API, what i could find is DefaultCHACallGraphDomain.scala which has no implementation of construct call graph.
As my purpose is using OPAL to construct call graph. Is there any demo or documents help me understanding existing CallGraphDomain in OPAL? currently, i can only find some class declaration.
I'll be really appreciated if anyone can give me some suggestions related this topic.
Thanks in advance.
Jiang
The interface that was shown in the paper doesn't exist anymore, so you can totally forget about it.
The default interface to get a CallGraph class is provided by the Project object you retrieve when you load the bytecode a Java project.
A general code Example:
val project = ... // a java project
val computedCallGraph = project.get(/* Some call graph key */)
val callGraph = computedCallGraph.callGraph // the final call graph interface.
The computed call graph contains several things. It contains the entry points, unresolved method calls, exceptions when something went wrong at the construction time and the actual call graph.
OPAL provides you several call graph algorithms, you can retrieve each by passing the corresponding call graph key to the Project's get method.
Currently, the following two keys are available and can be passed to Project.get (more information is available in the documentation of this classes):
CHACallGraphKey
VTACallGraphKey
Analysis mode - Library vs Application
To construct a valid call graph for a software project it depends on the project kind which analysis mode to chose. While applications provide complete information (except incomplete projects, class loading and so on), software libraries are intended to be used by other projects. However, those two different scenarios have to be kept in mind, when construction call graphs. More details can be found here: org.opalj.AnalysisModes
OPAL offers the following analysis modes:
DesktopApplication (safe for application call graphs)
LibraryWithClosePackagesAssumption (safe for call graphs that are used for security-insensitive analyses)
LibraryWithOpenPackagesAssumption (very conservative/safe for security analyses)
The analysis mode can be either configured in OPAL's config file or set as project setting at runtime. You can find the config file in the Common project under /src/main/resources/reference.conf.
All of those analysis modes are supported by the the CHACallGraphKey while VTACallGraphKey only supports applications so far.
NOTE: The interface may change in upcoming versions again.
I have a question related to V4L-DVB drivers. Following the
Building/Compiling the Latest V4L-DVB Source Code link, there are 3 ways to
compile. I am curious about the last approach (More "Manually
Intensive" Approach). It allows me to choose the components that I
wish to build and install using the "make menuconfig". Some of these components (i.e. "CONFIG_MEDIA_ATTACH") are used in pre-processor directives that define a function in one shape if defined, and a function in another if not defined (i.e.
dvb_attach, dvb_detach) in the resulting modules (i.e. dvb_core.ko)
that will be loaded by most of the DVB drivers. What happens if there are two
drivers (*.ko modules) on the same host machine, one that needs dvb_core.ko with
CONFIG_MEDIA_ATTACH defined and another that needs dvb_core.ko with
CONFIG_MEDIA_ATTACH undefined, is there a clean way to handle this?
What is also not clear to me is: Since the V4L compilation environment seems very customizable (by setting the .config file), if I develop a driver using V4L-DVB structures, there is a big chance that it has conflicts with other drivers since each driver has its own custom settings. Is my understanding correct?
Thanks!
Dave
I've seen that it's already implemented in Matlab R2013 in the form of Variant Subsystems, but budget and convenience don't show the upgrade necessary yet:
I am seeking a subsystem in which a concrete implementation can be selected prior to running the simulation, in Matlab R2007a.
A bunch of enabled subsystems along with a switch block connected to a masked variable would do the trick, however the whole family of selectable implementations must coexist inside the "container" subsystem.
Any workaround, other than upgrading to R2013?
Thank you.
I have come up with the following workaround.
1- Include all the possible implementations in a Library
2- Create a Configurable Subsystem block in the Library and edit it to include all the desired implementations
3- Right clicking in a Configurable Subsystem instance will show the "Block Choice" option where the desired implementation can be chosen.
Regardless of differences that may exist with respect to the Variant Subsystem solution when it comes to code generation, RT targets etc..., this solution works for me.
I have an emf model and i'd like to make a GMF editor to create instances of this metamodel.I'd like also some live constraints to avoid some connections between the components of my EMF model.e.g:My EMF consists of A,B,C,D components which derive from a General class called F and there is reference within F which connects F->F,as such this is able to provide me with connections in between the A,B,C,D components.
But when i am at the GMF editor i'd like a mechanism to avoid connection A->B and allow only connection A->C.
I read that this is able to be achieved with OCL language and link constraints that are able to be added at the gmfmap file.
But i couldn't find any tutorial with the vocabulary of OCL and examples doing that live validation
Any directions from someone?
After a deeper search I found a very useful and fast framework for validation. It is called Eugenia from the Epsilon group.
Eugenia lets you create all the appropriate files for the final GMF editor through a single file (extremely awesome,because otherwise you have to declare gfmtool, gmfgraph, etc by your own) and afterwards you can create a new EVL file which holds the constraints and the invariants of your model.The mapping is been doing easily by providing and extension point at your metamodel URI and all you have to do is to include your new plugin which containts the evl file at your final Eclipse configuration. http://www.eclipse.org/gmt/epsilon/doc/articles/evl-gmf-integration/
(Be careful, do not generate the diagram code as an RPC application because the RPC is not going to work. For any further information have a look here : http://giampow.blogspot.com/2010/06/eclipse-rcp-application-custom-problems.html )
Problem
Your organization has many separate applications, some of which interact with each other (to form "systems"). You need to deploy these applications to separate environments to facilitate staged testing (for example, DEV, QA, UAT, PROD). A given application needs to be configured slightly differently in each environment (each environment has a separate database, for example). You want this re-configuration to be handled by some sort of automated mechanism so that your release managers don't have to manually configure each application every time it is deployed to a different environment.
Desired Features
I would like to design an organization-wide configuration solution with the following properties (ideally):
Supports "one click" deployments (only the environment needs to be specified, and no manual re-configuration during/after deployment should be necessary).
There should be a single "system of record" where a shared environment-dependent property is specified (such as a database connection string that is shared by many applications).
Supports re-configuration of deployed applications (in the event that an environment-specific property needs to change), ideally without requiring a re-deployment of the application.
Allows an application to be run on the same machine, but in different environments (run a PROD instance and a DEV instance simultaneously).
Possible Solutions
I see two basic directions in which a solution could go:
Make all applications "environment aware". You would pass the environment name (DEV, QA, etc) at the command line to the app, and then the app is "smart" enough to figure out the environment-specific configuration values at run-time. The app could fetch the values from flat files deployed along with the app, or from a central configuration service.
Applications are not "smart" as they are in #1, and simply fetch configuration by property name from config files deployed with the app. The values of these properties are injected into the config files at deploy-time by the install program/script. That install script takes the environment name and fetches all relevant configuration values from a central configuration service.
Question
How would/have you achieved a configuration solution that solves these problems and supports these desired features? Am I on target with the two possible solutions? Do you have a preference between those solutions? Also, please feel free to tell me that I'm thinking about the problem all wrong. Any feedback would be greatly appreciated.
We've all run into these kinds of things, particularly in large organizations. I think it's most important to manage your own expectations first, and also ask whether it's really necessary to tell every system and subsystem on a given box to "change to DEV mode" or "change to PROD mode". My personal recommendation is as follows:
Make individual boxes responsible for a different stage - i.e. "this is a DEV box", and "this is a PROD box".
Collect as much of the configuration that differs from box to box in one location, even if it requires soft links or scripts that collect the information to then print out.
A. This way, you can easily "dump this box's configuration" in two places and see what differs, for example after a new deployment.
B. You can also make configuration changes separate from software changes, at least to some degree, which is a good way to root out bugs that happen at release time.
Then have everything base its configuration on something/somewhere that is not baked-in or hard-coded - just make sure to collect and document it in that one location. It almost doesn't matter what the mechanism is, which is a good thing, because some systems just don't want to be forced to use some mechanisms or others.
Sorry if this is too general an answer - the question was very general. I've worked in several large software-based organizations before, and this seemed to be the best approach. Using a standalone server as "one unit of deployment" is the most realistic scenario (though sometimes its expensive), since applications affect each other, and no matter how careful you are, you destabilize a whole system when you move any given gear or cog.
The alternative gets very complex very quickly. You need to start rewriting the applications that you have control over in order to have them accept a "DEV" switch, and you end up adding layers of kludge to the ones you don't have control over. Usually, the ones you don't have control over at least base their properties on something defined on a system-wide level, unless they are "calling the mothership for instructions".
It's easier to redirect people to a remote location and have them "use DEV" vs "use PROD" than it is to "make this machine run like DEV" vs "make this machine run like PROD". And if you're mixing things up, like having a DEV task run together on the same box as a PROD task, then that's not a realistic scenario anyways: I guarantee that eventually you will be granting illegal DEV-only access to somebody on PROD, and you'll have a DEV task wipe out a PROD database.
Hope this helps. Let me know if you'd like to discuss more specifics involved.
I personally prefer solution 2 (the app should know itself, by its configuration, what environment it is running in). With solution 1 (pass the environment name as a startup parameter) the danger of using the wrong environment specifier is much too high. Accessing the TEST database from PROD code and vice versa may cause mayhem, if the two installed code bases are not of the same version, as is often the case.
My current project uses solution 1, but I don't like that. A previous project I worked on used a variation of solution 2: The build process generated one setup file for every environment, making sure that they contained the same code base but appropriate configuration paramters. That worked like a charm, but I know it contradicts the paradigm that the "exact same build files must be deployed everywhere".
I think I have asked a related, self-answered, question, before I read this one : How to organize code so that we can move and update it without having to edit the location of the configuration file? . So, on that basis, I provide an answer here. I don't like the idea of "smart" application (solution 1 here) for such a simple task as finding environment settings. It seems a complicated framework for something that should be simple. The idea of an install script (solution 2 here) is powerful, but it is useful to allow the user to change the content of the config file, but would it allow to change the location of this config file? What is this "central configuration service", where is it located? My answer is that I would go with option 2, if the goal is to set the content of the configuration file, but I feel that the issue of the location of this configuration file remains unanswered here.
If you're using JSON to store/transmit configuration (or can use JSON in your pre-deploy process to output to some other format) you can annotate key/property names for environment/context-specific values with arbitrary or environment-specific suffixes, and then dynamically prefer/discriminate them at build/deploy/run/render -time, while leaving un-annotated properties alone.
We have used this to avoid duplicating entire configuration files (with the associated problems well known) AND to reduce repetition. The technique is also perfect for internationalization (i18n) -- even within the same file, if desired.
Example, snippet of pre-processed JSON config:
var config = {
'ver': '1.0',
'help': {
'BLURB': 'This pre-production environment is not supported. Contact Development Team with questions.',
'PHONE': '808-867-5309',
'EMAIL': 'coder.jen#lostnumber.com'
},
'help#www.productionwebsite.com': {
'BLURB': 'Please contact Customer Service Center',
'BLURB#fr': 'S\'il vous plaît communiquer avec notre Centre de service à la clientèle',
'BLURB#de': 'Bitte kontaktieren Sie unseren Kundendienst!!1!',
'PHONE': '1-800-CUS-TOMR',
'EMAIL': 'customer.service#productionwebsite.com'
},
}
... and post-processed (in this case, at render time) given dynamic, browser-environment-known location.hostname='www.productionwebsite.com' and navigator.language of 'de'):
prefer(config,['www.productionwebsite.com','de']); // prefer(obj,string|Array<string>)
JSON.stringify(config); // {
'ver': '1.0',
'help': {
'BLURB': 'Bitte kontaktieren Sie unseren Kundendienst!!1!',
'PHONE': '1-800-CUS-TOMR',
'EMAIL': 'customer.service#productionwebsite.com'
}
}
If a non-annotated ('base') property has no competing annotated property, it is left alone (presumably global across environments) otherwise its value is replaced by an annotated value, if the suffix matches one of the inputs to the preference/discrimination function. Annotated properties that do not match are dropped entirely.
You can mix and match this behaviour to annotate configuration to achieve distinctions of global, default, specific that are (assuming you're sensible) readable with zero/minimal duplication.
The single, recursive prefer() function (as we're calling it, lacking the need or desire to make an entire project/framework out of it) we've developed so far (see jsFiddle, with inline docs) goes a bit further than this simple example, and (explained in greater detail here) handles deeply-nested configuration objects, as well as preferential ordering and (if you need to stay flat) combination of suffixes.
The function relies on JS ability to reference object properties as strings, dynamically, and tolerate # and & delimiters in property names which are not valid in dot-notation syntax but consequently (help) prevent developers from breaking this technique by accidentally referring to pre-processed/annotated attributes in code (unless they, non-conventionally don't prefer to use dot-notation.)
We have yet to have this break anything for us, nor have we been schooled on any fundamental flaws of this technique, beyond irresponsible/unintended usage or investment/fondness for existing frameworks/techniques that pre-exist. We have also not profiled it for performance (we only tend to run this once per build/session, etc.) so in your own usage, YMMV.
Most configurations transmitted client-side of course would not want to contain sensitive pre-production values, so one could (should!) use the same function to generate a production-only version (with no annotations) in pre-deploy, while still enjoying a SINGLE configuration file upstream in your process.
Further, if you're doing this for i18n, you may not want the entire wad going over the wire, so could process it server-side (cached or live, etc.) or pre-process it in build/deploy by splitting into separate files, but STILL enjoying a single source of truth as early in your workflow as possible.
We have not explored implementing the same function in Java (or C#, PERL, etc.) assuming it's even possible (with some exotic reflection maybe?) but a build environment that includes NodeJS could farm that step out easily.
Well if it suits your needs and you have no problem of storing the connection strings in the source control repository, you could create files like:
appsettings.dev.json
appsettings.qa.json
appsettings.staging.json
And choose the right one in the deployment script and rename it to the actual appsettings.json, which is then read by your app.