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In software engineering, the blackboard pattern is a behavioral design pattern[1] that provides a computational framework for the design and implementation of systems that integrate large and diverse specialized modules, and implement complex, non-deterministic control strategies.[2][1]

This pattern was identified by the members of the Hearsay-II project and first applied to speech recognition.[2]

Structure

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The blackboard model defines three main components:

  • blackboard—a structured global memory containing objects from the solution space
  • knowledge sources—specialized modules with their own representation
  • control component—selects, configures and executes modules.[2]

Implementation

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The first step is to design the solution space (i.e. potential solutions) that leads to the blackboard structure. Then, knowledge sources are identified. These two activities are closely related.[2]

The next step is to specify the control component; it generally takes the form of a complex scheduler that makes use of a set of domain-specific heuristics to rate the relevance of executable knowledge sources.[2]

System Structure[2]

Applications

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Usage-domains include:

Consequences

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The blackboard pattern provides effective solutions for designing and implementing complex systems where heterogeneous modules have to be dynamically combined to solve a problem. This provides non-functional properties such as:

  • reusability
  • changeability
  • robustness.[2]

The blackboard pattern allows multiple processes to work closer together on separate threads, polling and reacting when necessary.[1]

See also

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References

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  1. ^ a b c "Blackboard Design Pattern". Microsoft TechNet. Microsoft. Retrieved 5 February 2016.
  2. ^ a b c d e f g h Lalanda, P. (1997), Two complementary patterns to build multi-expert systems (PDF), Orsay, France: Thomson CSF Corporate Research Laboratory

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