Code repository for master thesis about example-driven DSML design http://msdl.cs.mcgill.ca/people/lucas

Lucas Heer ddde9bd983 last round of evolution fixes for attributes 7 gadi atpakaļ
bootstrap 0a72f86596 merged model move from testing branch, can now move model from one location to another (useful to reuse example models as instance models 7 gadi atpakaļ
doc 861f5c6c52 Update documentation for new activity execution 7 gadi atpakaļ
evolution ddde9bd983 last round of evolution fixes for attributes 7 gadi atpakaļ
hybrid_server 8d26076636 Fixed "instruction pointer not found" error 7 gadi atpakaļ
integration 8d0bcb1616 Work around some issues 7 gadi atpakaļ
interface c730e25e10 Remoded non-existing function 7 gadi atpakaļ
kernel 364bf7dffd New bootstrapping process: no more exec with initializers in a dictionary, but instead directly invoke the global assignment 7 gadi atpakaļ
model 5e0500de3f Revert "Merge branch 'DEVS' into testing" 7 gadi atpakaļ
models 4639a78203 reworked edge mandatory constraint, some related bug fixes 7 gadi atpakaļ
scripts 8ca854edfc Switch raw_input to input when needed. 7 gadi atpakaļ
services 39c849d8ef Fixed some bugs related to AL models 7 gadi atpakaļ
sketchUI ddde9bd983 last round of evolution fixes for attributes 7 gadi atpakaļ
state 05bcbd450f Fixed test for MvS with new size of datatype 7 gadi atpakaļ
unit 8d0bcb1616 Work around some issues 7 gadi atpakaļ
wrappers 537f44a1f8 forbid deleting mandatory types and attributes in instance models 7 gadi atpakaļ
.gitattributes b3d374390d Make .gz files merge properly 8 gadi atpakaļ
.gitignore b219a79554 started on UI for instance modeling 7 gadi atpakaļ
README.md 592282cbcf Massive cleanup 8 gadi atpakaļ
alc_io.py ec9b3d7dd6 sync my files after latest merge from upstream, cleaned up a bit, adapted code to new exceptions 7 gadi atpakaļ
alc_io.xml ec9b3d7dd6 sync my files after latest merge from upstream, cleaned up a bit, adapted code to new exceptions 7 gadi atpakaļ
commons.py ddde9bd983 last round of evolution fixes for attributes 7 gadi atpakaļ
main.py 4639a78203 reworked edge mandatory constraint, some related bug fixes 7 gadi atpakaļ
sum_times.py bfcb1fb5d4 More general code to sum times 8 gadi atpakaļ
test_printer.py 8d26076636 Fixed "instruction pointer not found" error 7 gadi atpakaļ
upload_image_as_cs.py c1f1b1ccf9 added script to manually upload an image file as concrete syntax icon for a node, also finished fetching and displaying this image in UI 7 gadi atpakaļ
verifier.py 4e5cfe72ff check if local transformation breaks conformance for attributes, nodes and edges. If it does, repair it automatically 7 gadi atpakaļ

README.md

Installation

Installing the Modelverse is unnecessary, as it is mere Python code and doesn't use installation scripts. All scripts which are generally useful are found in the 'scripts' directory, and are written in OS-independent Python code.

You will, however, need to install a dependency: the SCCD compiler and runtime.

Starting up the Modelverse

Starting up the Modelverse is easy: simply execute the scripts/run_local_modelverse.py script, with as parameter the port you want to use. By default, port 8001 is used.

Communicating with the Modelverse

Now that the Modelverse is running, you will want to communicate with it! To do this, you can use whatever tool you want, as long as it can send and receive XML/HTTPRequests. For example, a mere internet browser can already communicate with the Modelverse, though not in the most user-friendly way.

A nicer way is through the Python prompt script scripts/prompt.py. After that, it will print out all the output of the Modelverse, and send in all your queries directly to the Modelverse.

Python wrapper

To automatically communicate with the Modelverse in a programmatic way, a Python wrapper is provided. This wrapper is found in wrappers/modelverse.py, and provides Python functions that make the necessary Modelverse requests. At the moment, not all functions are implemented in the wrapper yet.

Performance

Performance of the Modelverse is currently rather low. This is primarily caused by the reliance on the action language, which is an explicitly modelled (and interpreted) language. Additionally, the Modelverse runs remotely, meaning that all requests have to pass over the network. Even when this is executed on the same machine, this causes quite some overhead.

Additional documentation

Some additional documentation can be found online in the Modelverse techreport, describing the internal workings of the Modelverse, as well as a brief introduction on how to use it. There is also in-depth documentation describing how to use the Modelverse and its various languages.

Tests

Running the tests is easy: simply execute scripts/run_tests.py in the main modelverse folder. This will invoke the necessary build commands (to create bootstrapping code etc.) and call the tests for each individual aspect of the Modelverse. Note that testing is done using py.test, which is the only dependency of the Modelverse (and only for tests, of course).

Using PyPy

Since all scripts chain the invocation with the same interpreter as originally invoking the script, you will need to install py.test for PyPy. Assuming that you already have PyPy installed, you can simply install py.test using these commands:

wget https://msdl.uantwerpen.be/files/get-pip.py
pypy get-pip.py --user
pypy -m pip install pytest --user

From then on, you can simply invoke all tests in PyPy using:

pypy scripts/run_tests.py