EASY Meta-programming with Rascal

Abstract

Abstract. Rascal is a new language for meta-programming and is intended to solve problems in the domain of source code analysis and transformation. In this article we give a high-level overview of the language and illustrate its use by many examples. Rascal is a work in progress both regarding implementation and documentation. More information is available at http://www.meta-environment.org/MetaEnvironment/Rascal.Key words: source code analysis, source code transformation, metaprogramming. A New Language for Meta-ProgrammingMeta-programs are programs that analyze, transform or generate other programs. Ordinary programs work on data; meta-programs work on programs. The range of programs to which meta-programming can be applied is large: from programs in standard languages like C and Java to domain-specific languages for describing highlevel system models or applications in specialized areas like gaming or finance. In some cases, even test results or performance data are used as input for meta-programs. Rascal is a new language for meta-programming, this is the activity of writing meta-programs. The EASY ParadigmMany meta-programming problems follow a fixed pattern. Starting with some input system (a black box that we usually call system-of-interest), first relevant information is extracted from it and stored in an internal representation. This internal representation is then analyzed and used to synthesize results. If the synthesis indicates this, these steps can be repeated over and over again. These steps are shown in Figure 1.1, "EASY: the Extract-Analyze-Synthesize Paradigm". This is an abstract view on solving meta-programming problems, but is it uncommon? No, so let's illustrate it with a few examples. Finding security breachesAlice is system administrator of a large online marketplace and she is looking for security breaches in her system. The objects-of-interest are the system's log files. First relevant entries are extracted. This will include, for instance, messages from the SecureShell demon that reports failed login attempts. From each entry login name and originating IP address are extracted and put in a table (the internal representation in this example). These data are analyzed by detecting duplicates and counting frequencies. A Forensic DSL compilerBernd is a senior software engineer working at the Berlin headquarters of a forensic investigation lab of the German government. His daily work is to find common patterns in files stored on digital media that have been confiscated during criminal investigations. Text, audio and video files are stored in zillions of different data formats and each data format requires its own analysis technique. For each new investigation ad hoc combinations of tools are used. This makes the process very labour-intensive and errorprone. Bernd convinces his manager that designing a new domain-specific language (DSL) for forensic investigations may relieve the pressure on their lab. After designing the DSL---let's call it DERRICK---he makes an EASY implementation for it....

Triple Graph Grammars in the Large for Translating Satellite Procedures

“…Using these systems is quite similar to our approach, which can be seen, e. g., in the Extract-Analyze-Synthesise (EASY) Paradigm for Rascal [20]. Both, the source and the target language, are specified in some form of grammar formalism and the transformation between the languages is given by a set of transformation rules, where all the abovementioned systems use some sorts of rewriting rules, which are specified in a textual syntax.…”

Towards multilingual programming environments

“…The Rascal metaprogramming language [19,20] was specifically designed to create source code models and map source code to these models. Three use cases, namely reverse engineering, refactoring tools and engineering of domain specific languages, have been the inspiration of its design.…”

“…For instance, containment is modeled in Rascal using a relation: rel Metaprogramming. Rascal's design is inspired by the Extract-Analyze-SYnthesize paradigm 4 (EASY) [20]. Many of the use cases for Rascal follow the structure of extracting source code facts, analyzing them and synthesizing a result.…”

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

“…That is, we developed a designated extractor, using the Rascal [11] meta-programming language, so that the following ANTLR constructs are abstracted away: Also some minor notational features like character class negation ( ∼ ) or range operator (..) needed to be translated into basic context-free grammar notation. Tokens defined as terminals were merged with the normal grammar rules.…”