The Meta-Environment is a flexible framework for language development, source code analysis and source code transformation. We highlight new features and demonstrate how the system supports key functionalities for software evolution: fact extraction, software analysis, visualization, and software transformation.

Abstract. Analysis and renovation of large software portfolios requires syntax analysis of multiple, usually embedded, languages and this is beyond the capabilities of many standard parsing techniques. The traditional separation between lexer and parser falls short due to the limitations of tokenization based on regular expressions when handling multiple lexical grammars. In such cases scannerless parsing provides a viable solution. It uses the power of context-free grammars to be able to deal with a wide variety of issues in parsing lexical syntax. However, it comes at the price of less efficiency. The structure of tokens is obtained using a more powerful but more time and memory intensive parsing algorithm. Scannerless grammars are also more non-deterministic than their tokenized counterparts, increasing the burden on the parsing algorithm even further. In this paper we investigate the application of the Right-Nulled Generalized LR parsing algorithm (RNGLR) to scannerless parsing. We adapt the Scannerless Generalized LR parsing and filtering algorithm (SGLR) to implement the optimizations of RNGLR. We present an updated parsing and filtering algorithm, called SRNGLR, and analyze its performance in comparison to SGLR on ambiguous grammars for the programming languages C, Java, Python, SASL, and C++. Measurements show that SRNGLR is on average 33% faster than SGLR, but is 95% faster on the highly ambiguous SASL grammar. For the mainstream languages C, C++, Java and Python the average speedup is 16%.

Abstract. We discuss generalisations of bottom up parsing, emphasising the relative costs for real programming languages. Our goal is to provide a roadmap of the available approaches in terms of their space and time performance for programming language applications, focusing mainly on GLR style algorithms. It is well known that the original Tomita GLR algorithm fails to terminate on hidden left recursion: here we analyse two approaches to correct GLR parsing (i) the modification due to Farshi that is incorporated into Visser's work and (ii) our own right-nullable GLR (RNGLR) algorithm, showing that Farshi's approach can be expensive. We also present results from our new Binary RNGLR algorithm which is asymptotically the fastest parser in this family and show that the recently reported reduction incorporated parsers can require automata that are too large to be practical on current machines.

The Grammar Tool Box is a toolset for manipulating Context Free Grammars and objects associated with them such as parsers, languages and derivations. GTB has three main rôles: as a pedagogic tool; as an experimental platform for novel algorithms and representations; and as a production tool for translator front end generation. In this paper we give an overview of GTB and its companion Java-based animator tool PAT. We illustrate the use of the toolset in the construction of a comparative study of three variants of the Tomita-style GLR parsing algorithm running on LR(0), SLR(1) and LR(1) tables for ANSI-C, ISO-Pascal and IBM VS-COBOL, and give results showing the size of the structures constructed by these parsers and the amount of searching required during the parse, which abstracts their runtime.

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