Ambiguity Detection: Scaling to Scannerless

Static ambiguity detection would be an important aspect of language workbenches for textual software languages. However, the challenge is that automatic ambiguity detection in context-free grammars is undecidable in general. Sophisticated approximations and optimizations do exist, but these do not scale to grammars for so-called ``scannerless parsers'', as of yet. We extend previous work on ambiguity detection for context-free grammars to cover disambiguation techniques that are typical for scannerless parsing, such as longest match and reserved keywords. This paper contributes a new algorithm for ambiguity detection in character-level grammars, a prototype implementation of this algorithm and validation on several real grammars. The total run-time of ambiguity detection for character-level grammars for languages such as C and Java is significantly reduced, without loss of precision. The result is that efficient ambiguity detection in realistic grammars is possible and may therefore become a tool in language workbenches

Static, Lightweight Includes Resolution for PHP

Dynamic languages include a number of features that are challenging to model properly in static analysis tools. In PHP, one of these features is the include expression, where an arbitrary expression provides the path of the file to include at runtime. In this paper we present two complementary analyses for statically resolving PHP includes, one that works at the level of individual PHP files and one targeting PHP programs, possibly consisting of multiple scripts. To evaluate the effectiveness of these analyses we have applied the first to a corpus of 20 open-source systems, totaling more than 4.5 million lines of PHP, and the second to a number of programs from a subset of these systems. Our results show that, in many cases, includes can be either resolved to a specific file or a small subset of possible files, enabling better IDE features and more advanced program analysis tools for PHP

Ambiguity Detection: Scaling to Scannerless

Static ambiguity detection would be an important aspect of language workbenches for textual software languages. However, the challenge is that automatic ambiguity detection in context-free grammars is undecidable in general. Sophisticated approximations and optimizations do exist, but these do not scale to grammars for so-called ``scannerless parsers'', as of yet. We extend previous work on ambiguity detection for context-free grammars to cover disambiguation techniques that are typical for scannerless parsing, such as longest match and reserved keywords. This paper contributes a new algorithm for ambiguity detection in character-level grammars, a prototype implementation of this algorithm and validation on several real grammars. The total run-time of ambiguity detection for character-level grammars for languages such as C and Java is significantly reduced, without loss of precision. The result is that efficient ambiguity detection in realistic grammars is possible and may therefore become a tool in language workbenches

Study of auroral dynamics with combined spacecraft and incoherent scatter radar data

The objectives of this project were to study the coupling between the ionosphere and the magnetosphere, and to understand how this coupling was affected by changes in the solar wind. The data used consisted of satellite measurements coordinated with Sondrestrom incoherent scatter radar observations. We focused our efforts on the study of temporal and spatial changes in the dayside auroral precipitation and electric field

Language Parametric Module Management for IDEs

An integrated development environment (IDE) monitors all the changes that a user makes to source code modules and responds accordingly by flagging errors, by reparsing, by rechecking, or by recompiling modules and by adjusting visualizations or other information derived from a module. A module manager is the central component of the IDE that is responsible for this behavior. Although the overall functionality of a module manager in a given IDE is fixed, its actual behavior strongly depends on the programming languages it has to support. What is a module? How do modules depend on each other? What is the effect of a change to a module? We propose a concise design for a language parametric module manager: a module manager that is parameterized with the module behavior of a specific language. We describe the design of our module manager and discuss some of its properties. We also report on the application of the module manager in the construction of IDEs for the specification language ASF+SDF as well as for Java. Our overall goal is the rapid development (generation) of IDEs for programming languages and domain specific languages. The module manager presented here represents a next step in the creation of such generic language workbenches

Meta-Language Support for Type-Safe Access to External Resources

Meta-programming applications often require access to heterogeneous sources of information, often from different technological spaces (grammars, models, ontologies, databases), that have specialized ways of defining their respective data schemas. Without direct language support, obtaining typed access to this external, potentially changing, information is a tedious and error-prone engineering task. The Rascal meta-programming language aims to support the import and manipulation of all of these kinds of data in a type-safe manner. The goal is to lower the engineering effort to build new meta programs that combine information about software in unforeseen ways. In this paper we describe built-in language support, so called \textit{resources}, for incorporating external sources of data and their corresponding data-types while maintaining type safety. We demonstrate the applicability of Rascal resources by example, sho