[PERFO] Handling of cross-document refs has an important impact on performance

[cbrun]

From a decent size model, which have no inter document cross ref but quite a few internal references.
EObjects: 3894
References with values: 3121

And using:
String json = JsonResourceImpl.toJson(r, Collections.EMPTY_MAP);

Serialization of my model takes 77606 ms (77 secs) which seems a lot compared to serialization/deserialization using BinaryResource which takes about 400ms.

String size:7126813 time: 77606 ms.

After profiling in tracing mode, in my case it all comes down to : org.eclipse.sirius.emfjson.utils.GsonEObjectSerializer.docKindMany(EObject, EReference)
and the following code which, I assume, try to detect whether there is a cross document reference to serialize:

        Iterator<? extends InternalEObject> it = internalEList.iterator();
        while (referenceType != GsonEObjectSerializer.SKIP && referenceType != GsonEObjectSerializer.CROSS_DOC && it.hasNext()) {
            InternalEObject internalEObject = it.next();
            if (internalEObject.eIsProxy()) {
                referenceType = GsonEObjectSerializer.CROSS_DOC;
            } else {
                Resource resource = internalEObject.eResource();
                if (resource != this.helper.getResource() && resource != null) {
                    referenceType = GsonEObjectSerializer.CROSS_DOC;
                }
            }
        }

brute force approach of commenting out this code (which should not be used in my case) lead to

 String size:7126813 time: 746 ms.

which is 100 times faster, and give the exact same result.

[cbrun]

I guess some logic in org.eclipse.emf.ecore.resource.impl.BinaryResourceImpl.EObjectOutputStream.saveEObject(InternalEObject, Check) could be reused as it seems to handle the cross document references case correctly, while keeping good performances.

[cbrun]

After a slightly deeper analysis: the calling code resolve the reference list value, and iterates over it, and the submethod docKindMany(EObject, EReference) will do that again, leading to n*n complexity with n being the size of my list.