Crowdsourcing has emerged as a novel paradigm where humans are employed to perform computational tasks. In the context of Domain-Specific Modeling Language (DSML) development, where the involvement of end-users is crucial to assure that the resulting language satisfies their needs, crowdsourcing tasks could be defined to assist in the language definition process. By relying on the crowd, it is possible to show an early version of the language to a wider spectrum of users, thus increasing the validation scope and eventually promoting its acceptance and adoption. We propose a systematic method for creating crowdsourcing campaigns aimed at refining the graphical notation of DSMLs. The method defines a set of steps to identify, create and order the questions for the crowd. As a result, developers are provided with a set of notation choices that best fit end-users' needs. We also report on an experiment validating the approach.

Better call the crowd: Using crowdsourcing to shape the notation of domain-specific languages

Brambilla, Marco;Mauri, Andrea
2017-01-01

Abstract

Crowdsourcing has emerged as a novel paradigm where humans are employed to perform computational tasks. In the context of Domain-Specific Modeling Language (DSML) development, where the involvement of end-users is crucial to assure that the resulting language satisfies their needs, crowdsourcing tasks could be defined to assist in the language definition process. By relying on the crowd, it is possible to show an early version of the language to a wider spectrum of users, thus increasing the validation scope and eventually promoting its acceptance and adoption. We propose a systematic method for creating crowdsourcing campaigns aimed at refining the graphical notation of DSMLs. The method defines a set of steps to identify, create and order the questions for the crowd. As a result, developers are provided with a set of notation choices that best fit end-users' needs. We also report on an experiment validating the approach.
2017
SLE 2017 - Proceedings of the 10th ACM SIGPLAN International Conference on Software Language Engineering, co-located with SPLASH 2017
9781450355254
Crowdsourcing; Domain-specific languages; Modeldriven development; Computer Science Applications1707 Computer Vision and Pattern Recognition; Software
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1059298
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