Embedding Languages Without Breaking Tools

Domain-specific languages (DSLs) are increasingly used as embedded languages within general-purpose host languages. DSLs provide a compact, dedicated syntax for specifying parts of an application related to specialized domains. Unfortunately, such language extensions typically do not integrate well with the development tools of the host language. Editors, compilers and debuggers are either unaware of the extensions, or must be adapted at a non-trivial cost. We present a novel approach to embed DSLs into an existing host language by leveraging the underlying representation of the host language used by these tools. Helvetia is an extensible system that intercepts the compilation pipeline of the Smalltalk host language to seamlessly integrate language extensions. We validate our approach by case studies that demonstrate three fundamentally different ways to extend or adapt the host language syntax and semantics.

Practical Dynamic Grammars for Dynamic Languages

Grammars for programming languages are traditionally specified statically. They are hard to compose and reuse due to ambiguities that inevitably arise. PetitParser combines ideas from scannerless parsing, parser combinators, parsing expression grammars and packrat parsers to model grammars and parsers as objects that can be reconfigured dynamically. Through examples and benchmarks we demonstrate that dynamic grammars are not only flexible but highly practical.

The Design of XML-Based Model and Experiment Description Languages for Network Simulation

The Simulation Automation Framework for Experiments (SAFE) is a project created to raise the level of abstraction in network simulation tools and thereby address issues that undermine credibility. SAFE incorporates best practices in network simulationto automate the experimental process and to guide users in the development of sound scientific studies using the popular ns-3 network simulator. My contributions to the SAFE project: the design of two XML-based languages called NEDL (ns-3 Experiment Description Language) and NSTL (ns-3 Script Templating Language), which facilitate the description of experiments and network simulationmodels, respectively. The languages provide a foundation for the construction of better interfaces between the user and the ns-3 simulator. They also provide input to a mechanism which automates the execution of network simulation experiments. Additionally,this thesis demonstrates that one can develop tools to generate ns-3 scripts in Python or C++ automatically from NSTL model descriptions.

The Risk of Paradoxical Embolism (RoPE) Study: initial description of the completed database

BACKGROUND: Detecting a benefit from closure of patent foramen ovale in patients with cryptogenic stroke is hampered by low rates of stroke recurrence and uncertainty about the causal role of patent foramen ovale in the index event. A method to predict patent foramen ovale-attributable recurrence risk is needed. However, individual databases generally have too few stroke recurrences to support risk modeling. Prior studies of this population have been limited by low statistical power for examining factors related to recurrence. AIMS: The aim of this study was to develop a database to support modeling of patent foramen ovale-attributable recurrence risk by combining extant data sets. METHODS: We identified investigators with extant databases including subjects with cryptogenic stroke investigated for patent foramen ovale, determined the availability and characteristics of data in each database, collaboratively specified the variables to be included in the Risk of Paradoxical Embolism database, harmonized the variables across databases, and collected new primary data when necessary and feasible. RESULTS: The Risk of Paradoxical Embolism database has individual clinical, radiologic, and echocardiographic data from 12 component databases, including subjects with cryptogenic stroke both with (n = 1925) and without (n = 1749) patent foramen ovale. In the patent foramen ovale subjects, a total of 381 outcomes (stroke, transient ischemic attack, death) occurred (median follow-up 2·2 years). While there were substantial variations in data collection between studies, there was sufficient overlap to define a common set of variables suitable for risk modeling. CONCLUSION: While individual studies are inadequate for modeling patent foramen ovale-attributable recurrence risk, collaboration between investigators has yielded a database with sufficient power to identify those patients at highest risk for a patent foramen ovale-related stroke recurrence who may have the greatest potential benefit from patent foramen ovale closure.