Proceeding 2000 IEEE International Symposium on Visual Languages
DOI: 10.1109/vl.2000.874351
|View full text |Cite
|
Sign up to set email alerts
|

Efficient parsing of visual languages based on critical pair analysis and contextual layered graph transformation

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1
1

Citation Types

0
40
0

Publication Types

Select...
5
1
1

Relationship

0
7

Authors

Journals

citations
Cited by 49 publications
(40 citation statements)
references
References 3 publications
0
40
0
Order By: Relevance
“…Several applications using graph transformation need or already use negative application conditions (NACs) to express that certain structures at a given time are forbidden, e.g., [1][2][3][4][5]. In order to allow conflict detection and analysis for these applications, the theory already worked out for graph transformation systems (gts) without NACs should be generalized to gts with NACs.…”
Section: Introductionmentioning
confidence: 99%
“…Several applications using graph transformation need or already use negative application conditions (NACs) to express that certain structures at a given time are forbidden, e.g., [1][2][3][4][5]. In order to allow conflict detection and analysis for these applications, the theory already worked out for graph transformation systems (gts) without NACs should be generalized to gts with NACs.…”
Section: Introductionmentioning
confidence: 99%
“…In this way we ensure that the language defined by the parser is at least a sub-language of that defined by constraints. Critical pair analysis can be useful to optimise the visual language parser (see [7]). …”
Section: Discussionmentioning
confidence: 99%
“…In the approach of [6], a restricted form of Statecharts was defined using a pure graph grammar approach (no meta-models). For this purpose, they used a low level (LLG, concrete syntax) and a high level (HLG, abstract syntax) representation.…”
Section: Related Workmentioning
confidence: 99%
“…-Three node inheritance graphs 6 Fig. 4 shows an example meta-model triple, which is an extension of the attributed type triple graph in Fig.…”
Section: Definition 12 (Attributed Type Triple Graph With Inheritancementioning
confidence: 99%