Pending Evolution of Grammars

The classic approach to grammar manipulation is based on instant processing of grammar edits, which limits the kinds of grammar evolution scenarios that can be expressed with it. Treating transformation preconditions as guards poses limitations on concurrent changes of the same grammar, on reuse of evolution scripts, on expressing optionally executed steps, on batch processing and optimization of them, etc. We propose an alternative paradigm of evolution, where a transformation can be scheduled for later execution based on its precondition. This kind of extreme evolution can be useful for expressing scenarios that are impossible to fully automate within the classic or the negotiated transformation paradigms

Language Convergence Infrastructure

The process of grammar convergence involves grammar extraction and transformation for structural equivalence and contains a range of technical challenges. These need to be addressed in order for the method to deliver useful results. The paper describes a DSL and the infrastructure behind it that automates the convergence process, hides negligible back-en

A Unified Format for Language Documents

We have analyzed a substantial number of language documentation artifacts, including language standards, language specifications, language reference manuals, as well as internal documents of standardization bodies. We have reverse-engineered their intended internal structure, and compared the results. The Language Document Format (LDF), was developed to specifically support the documentation domain. We have also integrated LDF into an engineering discipline for language documents including tool support, for example, for rendering language documents, extracting grammars and samples, and migrating existing documents into LDF. The definition of LDF, tool support for LDF, and LDF applications are freely available through SourceForge

Recovering grammar relationships for the Java language specification

Grammar convergence is a method that helps in discovering relationships between different grammars of the same language or different language versions. The key element of the method is the operational, transformation-based representation of those relationships. Given input grammars for convergence, they are transformed until they are structurally equal. The transformations are composed from primitive operators; properties of these operators and the composed chains provide quantitative and qualitative insight into the relationships between the grammars at hand. We describe a refined method for grammar convergence, and we use it in a major study, where we recover the relationships between all the grammars that occur in the different versions of the Java Language Specification (JLS). The relationships are represented as grammar transformation chains that capture all accidental or intended differences between the JLS grammars. This method is mechanized and driven by nominal and structural differences between pairs of grammars that are subject to asymmetric, binary convergence steps. We present the underlying operator suite for grammar transformation in detail, and we illustrate the suite with many examples of transformations on the JLS grammars. We also describe the extraction effort, which was needed to make the JLS grammars amenable to automated processing. We include substantial metadata about the convergence process for the JLS so that the effort becomes reproducible and transparent

Language Support for Megamodel Renarration

Megamodels may be difficult to understand because they reside at a high level of abstraction and they are graph-like structures that do not immediately provide means of order and decomposition as needed for successive examination and comprehension. To improve megamodel comprehension, we introduce modeling features for the recreation, in fact, renarration of megamodels. Our approach relies on certain operators for extending, instantiating, and otherwise modifying megamodels. We illustrate the approach in the context of megamodeling for Object/XML mapping (also known as XML data binding)

Comparison of Context-free Grammars Based on Parsing Generated Test Data

There exist a number of software engineering scenarios that essentially involve equivalence or correspondence assertions for some of the context-free grammars in the scenarios. For instance, when applying grammar transformations during parser development---be it for the sake of disambiguation or grammar-class compliance---one would like to preserve the generated language. Even though equivalence is generally undecidable for context-free grammars, we have developed an automated approach that is practically useful in revealing evidence of nonequivalence of grammars and discovering correspondence mappings for grammar nonterminals. The approach is based on systematic test data generation and parsing. We discuss two studies that show how the approach is used in comparing grammars of open source Java parsers as well as grammars from the course work for a compiler construction class

Comparison of Context-free Grammars Based on Parsing Generated Test Data

There exist a number of software engineering scenarios that essentially involve equivalence or correspondence assertions for some of the context-free grammars in the scenarios. For instance, when applying grammar transformations during parser development—be it for the sake of disambiguation or grammar-class compliance—one would like to preserve the generated language. Even though equivalence is generally undecidable for context-free grammars, we have developed an automated approach that is practically useful in revealing evidence of nonequivalence of grammars and discovering correspondence mappings for grammar nonterminals. Our approach is based on systematic test data generation and parsing. We discuss two studies that show how the approach is used in comparing grammars of open source Java parsers as well as grammars from the course work for a compiler construction class