Selecting the initial project

When setting the scope of the initial project it is critical to remember the objectives of the initial phase as outlined in earlier posts.  They are:

  1. Understand how artifacts from models integrate with existing artifacts
  2. Establish baseline testing activities
  3. Implement version control for new modeling artifacts
  4. Identify initial model and data architecture

The motivation behind these objectives is to determine how the models fit into your overall process.  To do this a system of appropriate complexity needs to be selected.

Integration

Within the software community the term “spaghetti code”(1) is used to describe software that is poorly partitioned lacking in well-defined interfaces.  puzzleAs the name implies integration with spaghetti code is difficult to break apart and difficult to integrate in a “clean” fashion.

For the first project a section of code should be selected with a reasonably clean interface.  The primary thing to avoid is a section of code that is heavily dependent on global data.  For the initial system, you are almost always integrating the new component into the existing system.  You should target components with a limited number of I/O and no or limited dependence on global data.

(Note: this section has assumed that you are working on a project with existing code that must be integrated with.)

Questions to ask

Will the model need to…

  1. call existing supporting functions?
  2. access global data?
  3. have context dependent execution?

The objective is to select a model that minimizes those requirements.

V&V

The verification(2) and validation tasks(3) play a key part in determining the scope of the initial project.  A good module would include

  1. Modal systems:  State charts with event based logic; allows for verification of context based execution.
  2. Conditional execution: If/then/else logic and enabled / disabled subsystems; allows for testing of model coverage
  3. Dynamic systems: Requires closed loop simulation with stimulus; validates the response characteristics of the system.

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For each of these three items the expected outcome should be fairly well know; the objective is not to find major errors, though this sometimes happens during initial projects, but to understand how you will do these activities.

Questions to ask

Will the model…

  1. produce measurable outputs?
  2. have multiple modes of operation?
  3. have dynamic responses?

The objective is to select a model that maximizes these requirements.

Version control

While one of the objectives of the initial adoption is to understand the artifacts that will be placed under version control this objective has little impact on the setting of the scope of the system.  Version control will be covered in a later post.  For now you can read one of my earlier linked in blog posts on version control.

Model and data architecture

The selected component should enable you to validate your selected architecture as outlined in the model architecture and data sections of this blog.architecture

Questions to ask

Will the model need to have…

  1. parameterizable data calculations.
  2. a functional interface definition.
  3. conditional execution interfaces.

The objective is to select a model that maximizes these requirements.

Complexity

The final metric to consider is algorithmic complexity.  While Model-Based Design allows people to develop more complex algorithms, for the initial project an algorithm that is well understood should be selected.  The objective is to examine how models fit into your development workflow, not to validate the capabilities of the model(4).

Questions to ask

The algorithm should be

  1. an existing or extension of an existing algorithm
  2. part of the project that will first deploy the Model-Based Design process.

The objective is to select a model that maximizes these requirements.

Footnotes

(1) I prefer the term “mushroom code” as it better explains how this code comes about.  It is generally code that has grown on top of well written code but due to organic decay is now difficult to take apart.

(2) Verification is intended to check that a product meets a set of design specifications

(3) Validation is intended to ensure a product, that meets the operational needs of the user.

(4) The capabilities of the modeling environment should be assessed; however this is a separate task from developing your Model-Based Design workflow.

(5) The header image is a reference to the song from “The Sound of Music: Do-Re-Mi ” which provides the advice on where to start.

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