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Composable languages for bioinformatics: the NYoSh experiment.

Manuele Simi1, Fabien Campagne1

  • 1The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, The Weill Cornell Medical College , New York, NY , United States of America.

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Summary
This summary is machine-generated.

Language Workbenches (LWBs) enable the creation of specialized programming languages for bioinformatics. NYoSh, built with an LWB, offers an enhanced alternative to shell scripting with improved development environments and seamless language composition.

Keywords:
GobyWebLanguage compositionLanguage workbenchNYoShScripting language

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Area of Science:

  • Software Engineering
  • Bioinformatics
  • Programming Language Design

Background:

  • Language Workbenches (LWBs) facilitate the development of domain-specific languages and seamless language composition.
  • Bioinformatics software development can benefit from advanced programming tools that support abstraction and modularity.

Purpose of the Study:

  • To evaluate the utility of LWBs for developing bioinformatics software solutions.
  • To demonstrate the potential of language composition in bioinformatics through a practical example.

Main Methods:

  • Developed NYoSh (Not Your ordinary Shell), a shell scripting alternative using an LWB (MPS).
  • Implemented NYoSh as a composition of multiple languages.
  • Integrated NYoSh with the GobyWeb system and developed an environment-aware editor.

Main Results:

  • NYoSh programs are as expressive and concise as shell scripts.
  • The LWB environment provided an advanced editor with semantic error detection and interactive compilation.
  • NYoSh supports seamless extension by end-users with new abstractions and language constructs.

Conclusions:

  • LWBs offer significant advantages for bioinformatics software development, including modern IDE features and language extensibility.
  • NYoSh provides a powerful and flexible alternative to traditional shell scripting for bioinformatics tasks.
  • Language composition within LWBs enhances the development of complex bioinformatics tools.