Models to Code: With No Mysterious Gaps

Book description

Learn how to translate an executable model of your application into running code. This is not a book about theory, good intentions or possible future developments. You'll benefit from translation technology and solid software engineering principles that are demonstrated with concrete examples using an open source tool chain.

Models don't deliver enough value if they are not on a direct path to code production. But to waste time building models that are merely pictures of your code doesn't add much value either. In this book, you'll translate detailed, yet platform-independent models that solve real application problems.

Using a pragmatic approach, Models to Code quickly dives into two case studies of Executable UML models. The models and code are extensively annotated and illustrate key principles that are emphasized throughout the book.

You'll work with code production using "C" as the implementation language and targeting microcomputer class processors. This might not be your particular target language or platform, but you can use you can use what you learn here to engineer or re-evaluate your own code translation system to dramatically increase the value of both your modeling and code generation solution.

Written by three leading experts, Models to Code is an exceptional resource for producing software by model translation—add it to your library today.

What You'll Learn

  • See how detailed models resolve ambiguity and contradiction common in requirements.

  • Examine how a model can be detailed enough to be executable and testable while remaining platform independent

  • Produce code from a model, leaving the model intact so it can be redeployed on new platforms or adapted to changing software and hardware technology.

  • Implement platform independent model execution rules in platform specific run-time code

Who This Book Is For

Modelers and systems engineers on active MBSE projects (using Executable UML or not), projects using Simulink, Matlab, Dymola, MatrixX and other math modelling tools.

Any developers with current or past model experience, professors, students, systems engineers, embedded systems developers, or anyone interested in learning more about software modelling.

Product information

  • Title: Models to Code: With No Mysterious Gaps
  • Author(s): Leon Starr, Andrew Mangogna, Stephen Mellor
  • Release date: June 2017
  • Publisher(s): Apress
  • ISBN: 9781484222164