forces and frictions affecting mde
DESCRIPTION
Empirical study on how engineers in the automotive industry work with model-driven engineering (MDE), presented at MODELS 2012 in Innsbruck.TRANSCRIPT
Forces and Frictions affecting MDE
An exploratory study by Adrian Kuhn, Gail Murphy and C. Albert Thompson University of British Columbia
Research partnership between General Motors, IBM and 8 Canadian universities.
www.necsis.ca
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We interviewed 20 People at GM.
Engineers and team leads.
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So here is what we learned…
Engineers seem to prefer the linear reading path of text over visual languages.
Complex tool chain leads to update cycles of days rather than minutes.
Domain experts invent novel systems, but the lack power to extend the language.
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But first, what is a model?
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In-‐silico simulaKon (physical model) Architecture (high-‐level model) — Class diagrams in IBM Rhapsody
Algorithm logic (low-‐level model) — Diagrams in MathWorks Simulink
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What is their MDE process?
Roles and artifacts.
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Sketch of the modeling process, taken from our interview notes.
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Domain experts invent novel algorithms, creating requirements documents and sketching software models.
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Software modelers implement algorithms, creating, or refining, software models based on requirements documents.
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Domain experts and modelers use ad-hoc model patches (i.e. Powerpoint slides with screenshots) to communicate changes!
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Code generation is automated, using code generation rules defined by a specialized team of code generation experts.
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Test engineers work with all artifacts, i.e. requirements documents, software models, generated sources and tests.
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ObservaKons
Forces and Frictions
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Force: trigger of essen.al complexity, likely independent of abstrac.on chosen. Fric.on: trigger of accidental complexity, namely complexity introduced by tools and language.
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Force: Teams are typically working on mul.ple versions of the same so?ware model. Fric.on: Yet engineers lack proper tooling to iden.fy and share differences.
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Force: Domain experts use a rich set of visual languages to invent novel algorithms. Fric.on: Yet they lack tool support to define their own liDle languages.
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Force: Inven.ng novel algorithms for vehicle control is an exploratory ac.vity. Fric.on: Yet tes.ng on vehicles suffers from lack of run.me changeability.
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Force: Engineers o?en need to navigate between requirements and models. Fric.on: Yet they there is no tool support for point-‐to-‐point traceability.
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Findings
What we learned …
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Engineers prefer the linear reading path of text over visual languages.
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Complex tool chain leads to update cycles of days rather than minutes.
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Domain experts invent novel systems, but lack the power to extend the language.
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Related work on user studies
• Hutchinson etal, ICSE 2011
• Mohagheghi and Dehlen, MODELS 2008
• Forward and Lethbridge, MISE 2008
• Heijstek and Chaudron, SEAA 2010
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So here is what we learned…
Engineers seem to prefer the linear reading path of text over visual languages.
Complex tool chain leads to update cycles of days rather than minutes.
Domain experts invent novel systems, but the lack power to extend the language.
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Download our papers"http://arxiv.org/abs/1207.0855 "http://arxiv.org/abs/1209.5800
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