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Title
Abstract
FAQs
Introduction
FMBD: A Formal MBD Method for Software Systems
Requirements Modeling and Analysis
Conclusions
References

On Model-Based Software Development

Profile image of Myla ArcherMyla Archer

2013

https://doi.org/10.1007/978-3-642-37395-4_4
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11 pages

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Abstract

Due to its many advantages, the growing use in software practice of Model-Based Development (MBD) is a promising trend. However, major problems in MBD of software remain, for example, the failure to integrate formal system requirements models with current code synthesis methods. This chapter introduces FMBD, a formal MBD process for building software systems which addresses this problem. The goal of FMBD is to produce high assurance software systems which are correct by construction. The chapter describes three types of models built during the FMBD process, provides examples from an avionics system to illustrate the models, and proposes three major challenges in MBD as topics for future research.

FAQs

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What are the primary benefits of using Model-Based Development (MBD)?add

MBD aids in early bug detection, enhancing understanding of system behavior, and supports automatic code generation. For instance, models allow for easier reasoning about system dynamics and facilitate formal verification.

How does the Abstract Requirements (AR) model improve software requirements modeling?add

The AR model simplifies representation by defining controlled variables as functions of modes and monitored variables. This approach enables checking for completeness and consistency, enhancing overall model reliability.

What are the challenges faced when synthesizing code from models?add

Synthesis often struggles due to insufficient formal requirement models and lack of necessary supplementary information for code generation. Tools like MathWork's Simulink exemplify these limitations by producing untrustworthy code due to absent formal semantics.

How does the FMBD process address the validation of model translations?add

FMBD employs translation validation techniques to confirm that each model translation, such as AR to CR, adheres to correctness criteria. This approach was notably enhanced by Pnueli et al. in 1999, establishing rigorous validation methods.

When utilizing MRICDF, how does polychronous modeling differ from synchronous approaches?add

MRICDF's polychronous modeling allows asynchronous processes to execute in parallel, unlike synchronous languages that mandate a strict time order. This flexibility facilitates the specification of complex real-world systems that synchronous models cannot adequately capture.

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